diff --git a/DESCRIPTION b/DESCRIPTION index 6485410f..4a24e828 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -104,4 +104,4 @@ VignetteBuilder: knitr, R.rsp RoxygenNote: 7.0.2 -Roxygen: list(markdown = TRUE, r6 = FALSE) +Roxygen: list(markdown = TRUE) diff --git a/R/Lrnr_arima.R b/R/Lrnr_arima.R index 2c66b17a..bdc29aff 100644 --- a/R/Lrnr_arima.R +++ b/R/Lrnr_arima.R @@ -41,8 +41,8 @@ Lrnr_arima <- R6Class( class = TRUE, public = list( initialize = function(order = NULL, - seasonal = list(order = c(0L, 0L, 0L), period = NA), - n.ahead = NULL, ...) { + seasonal = list(order = c(0L, 0L, 0L), period = NA), + n.ahead = NULL, ...) { super$initialize(params = args_to_list(), ...) } ), diff --git a/R/Lrnr_bartMachine.R b/R/Lrnr_bartMachine.R index 8f7bc351..7ed870fd 100644 --- a/R/Lrnr_bartMachine.R +++ b/R/Lrnr_bartMachine.R @@ -62,9 +62,9 @@ Lrnr_bartMachine <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(num_trees = 50, num_burn_in = 250, verbose = F, - alpha = 0.95, beta = 2, k = 2, q = 0.9, nu = 3, - num_iterations_after_burn_in = 1000, - prob_rule_class = 0.5, ...) { + alpha = 0.95, beta = 2, k = 2, q = 0.9, nu = 3, + num_iterations_after_burn_in = 1000, + prob_rule_class = 0.5, ...) { super$initialize(params = args_to_list(), ...) } ), diff --git a/R/Lrnr_base.R b/R/Lrnr_base.R index 7aa9b162..4e528d39 100644 --- a/R/Lrnr_base.R +++ b/R/Lrnr_base.R @@ -97,12 +97,16 @@ Lrnr_base <- R6Class( }, base_train = function(task, trained_sublearners = NULL) { + # trains learner to data assert_that(is(task, "sl3_Task")) # TODO: add error handling subsetted_task <- self$subset_covariates(task) + verbose <- getOption("sl3.verbose") + + if (!is.null(trained_sublearners)) { fit_object <- private$.train(subsetted_task, trained_sublearners) } else { @@ -182,8 +186,10 @@ Lrnr_base <- R6Class( train = function(task) { delayed_fit <- delayed_learner_train(self, task) + verbose <- getOption("sl3.verbose") + - return(delayed_fit$compute(job_type = sl3_delayed_job_type())) + return(delayed_fit$compute(job_type = sl3_delayed_job_type(), progress=verbose)) }, predict = function(task = NULL) { diff --git a/R/Lrnr_bilstm.R b/R/Lrnr_bilstm.R index 688b15ee..1d2a0cb7 100644 --- a/R/Lrnr_bilstm.R +++ b/R/Lrnr_bilstm.R @@ -31,16 +31,16 @@ Lrnr_bilstm <- R6Class( classname = "Lrnr_bilstm", inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(units = 4, - loss = "mean_squared_error", - optimizer = "adam", - batch_size = 1, - epochs = 500, - window = 5, - n.ahead = 1, - activation = "linear", - dense = 1, - dropout = 0, - ...) { + loss = "mean_squared_error", + optimizer = "adam", + batch_size = 1, + epochs = 500, + window = 5, + n.ahead = 1, + activation = "linear", + dense = 1, + dropout = 0, + ...) { params <- list( units = units, loss = loss, optimizer = optimizer, batch_size = batch_size, epochs = epochs, window = window, diff --git a/R/Lrnr_bound.R b/R/Lrnr_bound.R index 5bf3309d..42c43848 100644 --- a/R/Lrnr_bound.R +++ b/R/Lrnr_bound.R @@ -32,7 +32,7 @@ Lrnr_bound <- R6Class( class = TRUE, public = list( initialize = function(bound = 0.005, - ...) { + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_caret.R b/R/Lrnr_caret.R index 1f297914..6ed2a150 100644 --- a/R/Lrnr_caret.R +++ b/R/Lrnr_caret.R @@ -51,10 +51,10 @@ Lrnr_caret <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(algorithm, - method = "CV", - metric = NULL, - trControl = caret::trainControl(method = method), - ...) { + method = "CV", + metric = NULL, + trControl = caret::trainControl(method = method), + ...) { params <- list( method = algorithm, ... diff --git a/R/Lrnr_condensier.R b/R/Lrnr_condensier.R index 0ba4ee53..f4ee0281 100644 --- a/R/Lrnr_condensier.R +++ b/R/Lrnr_condensier.R @@ -53,17 +53,17 @@ Lrnr_condensier <- R6Class( class = TRUE, public = list( initialize = function(bin_method = c("equal.mass", "equal.len", "dhist"), - nbins = 5, - max_n_cat = 20, - pool = FALSE, - max_n_bin = NA_integer_, - parfit = FALSE, - bin_estimator = make_learner( - Lrnr_glm_fast, - family = binomial() - ), - intrvls = NULL, - ...) { + nbins = 5, + max_n_cat = 20, + pool = FALSE, + max_n_bin = NA_integer_, + parfit = FALSE, + bin_estimator = make_learner( + Lrnr_glm_fast, + family = binomial() + ), + intrvls = NULL, + ...) { params <- args_to_list() assert_that(is(bin_estimator, "Lrnr_base") || is( bin_estimator, diff --git a/R/Lrnr_cv.R b/R/Lrnr_cv.R index 397dbe30..3b760096 100644 --- a/R/Lrnr_cv.R +++ b/R/Lrnr_cv.R @@ -196,6 +196,7 @@ Lrnr_cv <- R6Class( .properties = c("wrapper", "cv"), .train_sublearners = function(task) { + verbose <- getOption("sl3.verbose") # if we get a delayed task, evaluate it # TODO: this is a kludge -- ideally we'd have Lrnr_cv work on delayed tasks like other learners @@ -216,7 +217,13 @@ Lrnr_cv <- R6Class( fold_number <- fold_index() revere_task <- task$revere_fold_task(fold_number) training_task <- train_task(revere_task, fold) - fit_object <- delayed_learner_train(learner, training_task) + if (verbose) { + delayed_name <- sprintf("CV %s fold %s", learner$name, fold_number) + } else { + delayed_name <- learner$name + } + + fit_object <- delayed_learner_train(learner, training_task, delayed_name) return(fit_object) } diff --git a/R/Lrnr_cv_selector.R b/R/Lrnr_cv_selector.R index 5d8d7166..5e286104 100644 --- a/R/Lrnr_cv_selector.R +++ b/R/Lrnr_cv_selector.R @@ -34,7 +34,7 @@ Lrnr_cv_selector <- R6Class( class = TRUE, public = list( initialize = function(loss_function = loss_squared_error, - ...) { + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_dbarts.R b/R/Lrnr_dbarts.R index 6e073446..bd6eda2c 100644 --- a/R/Lrnr_dbarts.R +++ b/R/Lrnr_dbarts.R @@ -92,6 +92,10 @@ #' \item{\code{keepcall}}{Logical; if \code{FALSE}, returned object will have #' \code{call} set to \code{call("NULL")}, otherwise the call used to #' instantiate BART.} +#' \item{\code{serializeable}}{Logical; if \code{TRUE}, loads the trees into R memory +#' so the fit object can be saved and loaded. See the section on "Saving" +#' in \code{\link[dbarts]{bart} NB: This is not currently working} +#' } #' } #' #' @template common_parameters @@ -102,8 +106,9 @@ Lrnr_dbarts <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(ndpost = 500, nskip = 100, - ntree = 200L, verbose = FALSE, keeptrees = TRUE, - ...) { + ntree = 200L, verbose = FALSE, keeptrees = TRUE, + serializeable = FALSE, + ...) { super$initialize(params = args_to_list(), ...) } ), @@ -129,6 +134,10 @@ Lrnr_dbarts <- R6Class( fit_object <- call_with_args(dbarts::bart, args) + if (self$params$serializeable) { + invisible(fit_object$fit$state) + } + return(fit_object) }, diff --git a/R/Lrnr_density_discretize.R b/R/Lrnr_density_discretize.R index 31d8a1a5..8c645943 100644 --- a/R/Lrnr_density_discretize.R +++ b/R/Lrnr_density_discretize.R @@ -31,7 +31,7 @@ Lrnr_density_discretize <- R6Class( class = TRUE, public = list( initialize = function(categorical_learner = NULL, type = "equal_mass", - n_bins = 20, ...) { + n_bins = 20, ...) { if (is.null(categorical_learner)) { categorical_learner <- make_learner(Lrnr_glmnet) } diff --git a/R/Lrnr_earth.R b/R/Lrnr_earth.R index 6b018ea0..e4ed04e9 100644 --- a/R/Lrnr_earth.R +++ b/R/Lrnr_earth.R @@ -60,8 +60,8 @@ Lrnr_earth <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(degree = 2, penalty = 3, pmethod = "backward", - nfold = 0, ncross = 1, minspan = 0, endspan = 0, - ...) { + nfold = 0, ncross = 1, minspan = 0, endspan = 0, + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_expSmooth.R b/R/Lrnr_expSmooth.R index c98eb710..f4e9f8a5 100644 --- a/R/Lrnr_expSmooth.R +++ b/R/Lrnr_expSmooth.R @@ -72,14 +72,14 @@ Lrnr_expSmooth <- R6Class( class = TRUE, public = list( initialize = function(model = "ZZZ", damped = NULL, alpha = NULL, - beta = NULL, gamma = NULL, phi = NULL, lambda = NULL, - additive.only = FALSE, biasadj = FALSE, - lower = c(rep(1e-04, 3), 0.8), - upper = c(rep(0.9999, 3), 0.98), - opt.crit = "lik", nmse = 3, bounds = "both", - ic = "aic", restrict = TRUE, - allow.multiplicative.trend = FALSE, - use.initial.values = FALSE, freq = 1, ...) { + beta = NULL, gamma = NULL, phi = NULL, lambda = NULL, + additive.only = FALSE, biasadj = FALSE, + lower = c(rep(1e-04, 3), 0.8), + upper = c(rep(0.9999, 3), 0.98), + opt.crit = "lik", nmse = 3, bounds = "both", + ic = "aic", restrict = TRUE, + allow.multiplicative.trend = FALSE, + use.initial.values = FALSE, freq = 1, ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_gam.R b/R/Lrnr_gam.R index 8d60d6cb..50b909ea 100644 --- a/R/Lrnr_gam.R +++ b/R/Lrnr_gam.R @@ -49,9 +49,9 @@ Lrnr_gam <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(formula = NULL, - family = NULL, - method = "GCV.Cp", - ...) { + family = NULL, + method = "GCV.Cp", + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_gbm.R b/R/Lrnr_gbm.R index f0e26f91..f066075c 100644 --- a/R/Lrnr_gbm.R +++ b/R/Lrnr_gbm.R @@ -46,7 +46,7 @@ Lrnr_gbm <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(n.trees = 10000, interaction.depth = 2, - shrinkage = 0.001, ...) { + shrinkage = 0.001, ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_glmnet.R b/R/Lrnr_glmnet.R index 538d6898..5dc2c588 100644 --- a/R/Lrnr_glmnet.R +++ b/R/Lrnr_glmnet.R @@ -48,7 +48,7 @@ Lrnr_glmnet <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(lambda = NULL, type.measure = "deviance", nfolds = 10, - alpha = 1, nlambda = 100, use_min = TRUE, ...) { + alpha = 1, nlambda = 100, use_min = TRUE, ...) { super$initialize(params = args_to_list(), ...) } ), diff --git a/R/Lrnr_grf.R b/R/Lrnr_grf.R index cdd69cb6..c98fdd15 100644 --- a/R/Lrnr_grf.R +++ b/R/Lrnr_grf.R @@ -75,19 +75,19 @@ Lrnr_grf <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(num.trees = 2000, - quantiles = c(0.1, 0.5, 0.9), - regression.splitting = FALSE, - clusters = NULL, - equalize.cluster.weights = FALSE, - sample.fraction = 0.5, - mtry = NULL, - min.node.size = 5, - honesty = TRUE, - alpha = 0.05, - imbalance.penalty = 0, - num.threads = 1, - quantiles_pred = 0.5, - ...) { + quantiles = c(0.1, 0.5, 0.9), + regression.splitting = FALSE, + clusters = NULL, + equalize.cluster.weights = FALSE, + sample.fraction = 0.5, + mtry = NULL, + min.node.size = 5, + honesty = TRUE, + alpha = 0.05, + imbalance.penalty = 0, + num.threads = 1, + quantiles_pred = 0.5, + ...) { super$initialize(params = args_to_list(), ...) } ), diff --git a/R/Lrnr_h2o_glm.R b/R/Lrnr_h2o_glm.R index 32b76589..a353b81a 100644 --- a/R/Lrnr_h2o_glm.R +++ b/R/Lrnr_h2o_glm.R @@ -74,8 +74,8 @@ Lrnr_h2o_glm <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(intercept = TRUE, standardize = TRUE, lambda = 0L, - max_iterations = 100, ignore_const_cols = FALSE, - missing_values_handling = "Skip", ...) { + max_iterations = 100, ignore_const_cols = FALSE, + missing_values_handling = "Skip", ...) { super$initialize(params = args_to_list(), ...) } ), diff --git a/R/Lrnr_h2o_grid.R b/R/Lrnr_h2o_grid.R index ec72ffff..1ac66553 100644 --- a/R/Lrnr_h2o_grid.R +++ b/R/Lrnr_h2o_grid.R @@ -49,9 +49,9 @@ Lrnr_h2o_grid <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(algorithm, seed = 1, distribution = NULL, - intercept = TRUE, standardize = TRUE, lambda = 0L, - max_iterations = 100, ignore_const_cols = FALSE, - missing_values_handling = "Skip", ...) { + intercept = TRUE, standardize = TRUE, lambda = 0L, + max_iterations = 100, ignore_const_cols = FALSE, + missing_values_handling = "Skip", ...) { super$initialize(params = args_to_list(), ...) } ), diff --git a/R/Lrnr_hal9001.R b/R/Lrnr_hal9001.R index 91fbe7e1..86f9b0a5 100644 --- a/R/Lrnr_hal9001.R +++ b/R/Lrnr_hal9001.R @@ -80,15 +80,15 @@ Lrnr_hal9001 <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(max_degree = 3, - fit_type = "glmnet", - n_folds = 10, - use_min = TRUE, - reduce_basis = NULL, - return_lasso = TRUE, - return_x_basis = FALSE, - basis_list = NULL, - cv_select = TRUE, - ...) { + fit_type = "glmnet", + n_folds = 10, + use_min = TRUE, + reduce_basis = NULL, + return_lasso = TRUE, + return_x_basis = FALSE, + basis_list = NULL, + cv_select = TRUE, + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_haldensify.R b/R/Lrnr_haldensify.R index 6c95325b..da520b35 100644 --- a/R/Lrnr_haldensify.R +++ b/R/Lrnr_haldensify.R @@ -42,9 +42,9 @@ Lrnr_haldensify <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(grid_type = c("equal_range", "equal_mass"), - n_bins = c(5, 10), - lambda_seq = exp(seq(-1, -13, length = 1000L)), - ...) { + n_bins = c(5, 10), + lambda_seq = exp(seq(-1, -13, length = 1000L)), + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_lstm.R b/R/Lrnr_lstm.R index 1c0785c4..a7799a80 100644 --- a/R/Lrnr_lstm.R +++ b/R/Lrnr_lstm.R @@ -32,16 +32,16 @@ Lrnr_lstm <- R6Class( classname = "Lrnr_lstm", inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(units = 4, - loss = "mean_squared_error", - optimizer = "adam", - batch_size = 1, - epochs = 500, - window = 5, - n.ahead = 1, - activation = "linear", - dense = 1, - dropout = 0, - ...) { + loss = "mean_squared_error", + optimizer = "adam", + batch_size = 1, + epochs = 500, + window = 5, + n.ahead = 1, + activation = "linear", + dense = 1, + dropout = 0, + ...) { params <- list( units = units, loss = loss, optimizer = optimizer, batch_size = batch_size, epochs = epochs, window = window, diff --git a/R/Lrnr_optim.R b/R/Lrnr_optim.R index 2e4a2414..01a14cfe 100644 --- a/R/Lrnr_optim.R +++ b/R/Lrnr_optim.R @@ -44,8 +44,8 @@ Lrnr_optim <- R6Class( class = TRUE, public = list( initialize = function(learner_function = metalearner_linear, - loss_function = loss_squared_error, - intercept = FALSE, init_0 = FALSE, ...) { + loss_function = loss_squared_error, + intercept = FALSE, init_0 = FALSE, ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_pca.R b/R/Lrnr_pca.R index 8f299e79..6d6c18ca 100644 --- a/R/Lrnr_pca.R +++ b/R/Lrnr_pca.R @@ -47,9 +47,9 @@ Lrnr_pca <- R6Class( class = TRUE, public = list( initialize = function(n_comp = 2, - center = TRUE, - scale. = TRUE, - ...) { + center = TRUE, + scale. = TRUE, + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_randomForest.R b/R/Lrnr_randomForest.R index 14019e67..2afec878 100644 --- a/R/Lrnr_randomForest.R +++ b/R/Lrnr_randomForest.R @@ -38,9 +38,9 @@ Lrnr_randomForest <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(ntree = 100, - keep.forest = TRUE, - nodesize = 5, maxnodes = NULL, - importance = FALSE, ...) { + keep.forest = TRUE, + nodesize = 5, maxnodes = NULL, + importance = FALSE, ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_ranger.R b/R/Lrnr_ranger.R index 541e437c..9ecae969 100644 --- a/R/Lrnr_ranger.R +++ b/R/Lrnr_ranger.R @@ -35,9 +35,9 @@ Lrnr_ranger <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(num.trees = 500, - write.forest = TRUE, - num.threads = 1, - ...) { + write.forest = TRUE, + num.threads = 1, + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_rfcde.R b/R/Lrnr_rfcde.R index ee80bf67..cb0ddd73 100644 --- a/R/Lrnr_rfcde.R +++ b/R/Lrnr_rfcde.R @@ -58,15 +58,15 @@ Lrnr_rfcde <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(n_trees = 1000, - node_size = 5, - n_basis = 31, - basis_system = "cosine", - min_loss_delta = 0.0, - fit_oob = FALSE, - z_grid = seq(0, 10, length.out = 100), - bandwidth = "auto", - output_type = "observed", - ...) { + node_size = 5, + n_basis = 31, + basis_system = "cosine", + min_loss_delta = 0.0, + fit_oob = FALSE, + z_grid = seq(0, 10, length.out = 100), + bandwidth = "auto", + output_type = "observed", + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_rpart.R b/R/Lrnr_rpart.R index b646e0bc..90c88c37 100644 --- a/R/Lrnr_rpart.R +++ b/R/Lrnr_rpart.R @@ -40,9 +40,9 @@ Lrnr_rpart <- R6Class( # you can define default parameter values here # if possible, your learner should define defaults for all required parameters initialize = function(model = FALSE, - x = FALSE, - y = FALSE, - ...) { + x = FALSE, + y = FALSE, + ...) { # this captures all parameters to initialize and saves them as self$params params <- args_to_list() super$initialize(params = params, ...) diff --git a/R/Lrnr_rugarch.R b/R/Lrnr_rugarch.R index eda38bf5..98d8740c 100644 --- a/R/Lrnr_rugarch.R +++ b/R/Lrnr_rugarch.R @@ -42,19 +42,19 @@ Lrnr_rugarch <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(variance.model = - list( - model = "sGARCH", garchOrder = c(1, 1), - submodel = NULL, external.regressors = NULL, - variance.targeting = FALSE - ), - mean.model = - list( - armaOrder = c(1, 1), include.mean = TRUE, - archm = FALSE, archpow = 1, arfima = FALSE, - external.regressors = NULL, archex = FALSE - ), - distribution.model = "norm", start.pars = list(), - fixed.pars = list(), n.ahead = NULL, ...) { + list( + model = "sGARCH", garchOrder = c(1, 1), + submodel = NULL, external.regressors = NULL, + variance.targeting = FALSE + ), + mean.model = + list( + armaOrder = c(1, 1), include.mean = TRUE, + archm = FALSE, archpow = 1, arfima = FALSE, + external.regressors = NULL, archex = FALSE + ), + distribution.model = "norm", start.pars = list(), + fixed.pars = list(), n.ahead = NULL, ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_screener_corP.R b/R/Lrnr_screener_corP.R index 18ef7fa1..c0edbf3d 100644 --- a/R/Lrnr_screener_corP.R +++ b/R/Lrnr_screener_corP.R @@ -31,8 +31,8 @@ Lrnr_screener_corP <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(method = "pearson", - minPvalue = 0.1, - minscreen = 2) { + minPvalue = 0.1, + minscreen = 2) { params <- args_to_list() super$initialize(params = params) } diff --git a/R/Lrnr_screener_corRank.R b/R/Lrnr_screener_corRank.R index ccc1e678..4632d2ba 100644 --- a/R/Lrnr_screener_corRank.R +++ b/R/Lrnr_screener_corRank.R @@ -30,7 +30,7 @@ Lrnr_screener_corRank <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(method = "pearson", - rank = 5) { + rank = 5) { params <- args_to_list() super$initialize(params = params) } diff --git a/R/Lrnr_screener_randomForest.R b/R/Lrnr_screener_randomForest.R index 9641a32f..349684aa 100644 --- a/R/Lrnr_screener_randomForest.R +++ b/R/Lrnr_screener_randomForest.R @@ -33,8 +33,8 @@ Lrnr_screener_randomForest <- R6Class( inherit = Lrnr_base, portable = TRUE, class = TRUE, public = list( initialize = function(nVar = 10, - ntree = 1000, - ...) { + ntree = 1000, + ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_sl.R b/R/Lrnr_sl.R index 7da1d736..2abb8b41 100644 --- a/R/Lrnr_sl.R +++ b/R/Lrnr_sl.R @@ -43,11 +43,15 @@ Lrnr_sl <- R6Class( class = TRUE, public = list( initialize = function(learners, metalearner = "default", folds = NULL, - keep_extra = TRUE, ...) { + keep_extra = TRUE, ...) { # kludge to deal with stack as learners if (inherits(learners, "Stack")) { learners <- learners$params$learners } + + if (inherits(learners, "Lrnr_base")) { + learners <- list(learners) + } params <- list( learners = learners, metalearner = metalearner, folds = folds, keep_extra = keep_extra, ... @@ -115,6 +119,11 @@ Lrnr_sl <- R6Class( coefficients = function() { self$assert_trained() return(coef(self$fit_object$cv_meta_fit)) + }, + + learner_fits = function() { + result <- self$fit_object$full_fit$learner_fits[[1]]$learner_fits + return(result) } ), @@ -145,7 +154,7 @@ Lrnr_sl <- R6Class( # make stack and CV learner objects learners <- self$params$learners - learner_stack <- do.call(Stack$new, learners) + learner_stack <- do.call(Stack$new, list(learners)) cv_stack <- Lrnr_cv$new(learner_stack, folds = folds, full_fit = TRUE) cv_stack$custom_chain(drop_offsets_chain) diff --git a/R/Lrnr_solnp.R b/R/Lrnr_solnp.R index 5c046e60..69895d2c 100644 --- a/R/Lrnr_solnp.R +++ b/R/Lrnr_solnp.R @@ -46,9 +46,9 @@ Lrnr_solnp <- R6Class( class = TRUE, public = list( initialize = function(learner_function = metalearner_linear, - loss_function = loss_squared_error, - make_sparse = TRUE, convex_combination = TRUE, - init_0 = FALSE, tol = 1e-5, ...) { + loss_function = loss_squared_error, + make_sparse = TRUE, convex_combination = TRUE, + init_0 = FALSE, tol = 1e-5, ...) { params <- args_to_list() super$initialize(params = params, ...) } diff --git a/R/Lrnr_svm.R b/R/Lrnr_svm.R index 34d0de36..ea970627 100644 --- a/R/Lrnr_svm.R +++ b/R/Lrnr_svm.R @@ -48,11 +48,11 @@ Lrnr_svm <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(scale = TRUE, - type = NULL, - kernel = "radial", - fitted = TRUE, - probability = FALSE, - ...) { + type = NULL, + kernel = "radial", + fitted = TRUE, + probability = FALSE, + ...) { # this captures all parameters to initialize and saves them as self$params params <- args_to_list() super$initialize(params = params, ...) diff --git a/R/Lrnr_tsDyn.R b/R/Lrnr_tsDyn.R index 64b51661..5c59cd37 100644 --- a/R/Lrnr_tsDyn.R +++ b/R/Lrnr_tsDyn.R @@ -82,25 +82,25 @@ Lrnr_tsDyn <- R6Class( portable = TRUE, class = TRUE, public = list( initialize = function(learner, m = 1, size = 1, lag = 1, d = 1, - include = "const", type = "level", n.ahead = NULL, - mL = m, mH = m, mM = NULL, thDelay = 0, - common = "none", ML = seq_len(mL), MM = NULL, - MH = seq_len(mH), nthresh = 1, trim = 0.15, - sig = 0.05, control = list(), r = 1, model = "VAR", - I = "level", beta = NULL, estim = "2OLS", - exogen = NULL, LRinclude = "none", - commonInter = FALSE, mTh = 1, gamma = NULL, - dummyToBothRegimes = TRUE, max.iter = 2, - ngridBeta = 50, ngridTh = 50, - th1 = list( - exact = NULL, int = c("from", "to"), - around = "val" - ), - th2 = list( - exact = NULL, int = c("from", "to"), - around = "val" - ), - beta0 = 0, ...) { + include = "const", type = "level", n.ahead = NULL, + mL = m, mH = m, mM = NULL, thDelay = 0, + common = "none", ML = seq_len(mL), MM = NULL, + MH = seq_len(mH), nthresh = 1, trim = 0.15, + sig = 0.05, control = list(), r = 1, model = "VAR", + I = "level", beta = NULL, estim = "2OLS", + exogen = NULL, LRinclude = "none", + commonInter = FALSE, mTh = 1, gamma = NULL, + dummyToBothRegimes = TRUE, max.iter = 2, + ngridBeta = 50, ngridTh = 50, + th1 = list( + exact = NULL, int = c("from", "to"), + around = "val" + ), + th2 = list( + exact = NULL, int = c("from", "to"), + around = "val" + ), + beta0 = 0, ...) { params <- args_to_list() super$initialize(params = params) } diff --git a/R/Pipeline.R b/R/Pipeline.R index 7ef265df..67fe755a 100644 --- a/R/Pipeline.R +++ b/R/Pipeline.R @@ -44,8 +44,16 @@ Pipeline <- R6Class( params <- list(learners = learners) learners_trained <- sapply(learners, `[[`, "is_trained") + learner_names <- sapply(learners, `[[`, "name") + if (any(duplicated(learner_names))) { + learner_names <- make.unique(learner_names, sep = "_") + } + private$.learner_names <- learner_names + + if (all(learners_trained)) { # we've been passed a list of existing fits so we're already fit + names(learners) <- learner_names private$.fit_object <- list(learner_fits = learners) private$.training_task <- learners[[1]]$training_task } @@ -86,15 +94,17 @@ Pipeline <- R6Class( learner_names <- sapply(learners, function(learner) learner$name) name <- sprintf("Pipeline(%s)", paste(learner_names, collapse = "->")) return(name) + }, + learner_fits = function() { + result <- self$fit_object$learner_fits + return(result) } ), private = list( .train_sublearners = function(task) { learners <- self$params$learners - learner_names <- sapply(learners, function(learner) learner$name) learner_fits <- as.list(rep(NA, length(learners))) - names(learner_fits) <- learner_names current_task <- task for (i in seq_along(learners)) { @@ -108,6 +118,7 @@ Pipeline <- R6Class( }, .train = function(task, trained_sublearners) { + names(trained_sublearners) <- private$.learner_names fit_object <- list(learner_fits = trained_sublearners) return(fit_object) }, @@ -128,6 +139,8 @@ Pipeline <- R6Class( # current_task is now the task for the last fit, so we can just do this predictions <- current_fit$base_predict(current_task) return(predictions) - } + }, + + .learner_names = NULL ) ) diff --git a/R/Stack.R b/R/Stack.R index 0cdd5d1f..b19b5b4d 100644 --- a/R/Stack.R +++ b/R/Stack.R @@ -87,6 +87,10 @@ Stack <- R6Class( # name = paste(learner_names, collapse="x") name <- "Stack" return(name) + }, + learner_fits = function() { + result <- self$fit_object$learner_fits + return(result) } ), @@ -123,6 +127,10 @@ Stack <- R6Class( if (all(is_error)) { stop("All learners in stack have failed") } + + learner_names <- private$.learner_names[!is_error] + names(trained_sublearners) <- learner_names + fit_object <- list( learner_fits = trained_sublearners, learner_errors = learner_errors, is_error = is_error diff --git a/R/Variable_Type.R b/R/Variable_Type.R index c8825ba7..0646fd6c 100644 --- a/R/Variable_Type.R +++ b/R/Variable_Type.R @@ -8,7 +8,7 @@ Variable_Type <- R6Class( class = TRUE, public = list( initialize = function(type = NULL, levels = NULL, bounds = NULL, x = NULL, - pcontinuous = getOption("sl3.pcontinuous")) { + pcontinuous = getOption("sl3.pcontinuous")) { if (is.null(type)) { if (is.null(x)) { stop("type not specified, and no x from which to infer it") diff --git a/R/learner_helpers.R b/R/learner_helpers.R index 9e20af2e..244b51e0 100644 --- a/R/learner_helpers.R +++ b/R/learner_helpers.R @@ -35,14 +35,20 @@ learner_train <- function(learner, task, trained_sublearners) { } #' @rdname learner_helpers -#' +#' @param name a more detailed name for this delayed task, if necessary #' @export # -delayed_learner_train <- function(learner, task) { +delayed_learner_train <- function(learner, task, name = NULL) { trained_sublearners <- learner$train_sublearners(task) train_delayed <- delayed_fun(learner_train)(learner, task, trained_sublearners) - train_delayed$name <- learner$name + + if (is.null(name)) { + name <- learner$name + } + + train_delayed$name <- name + if (!is.null(trained_sublearners)) { # if a learner is sequential assume the train step is minimal and don't # parallelize diff --git a/R/sl3_Task.R b/R/sl3_Task.R index 8f3ad932..81d2ce5e 100644 --- a/R/sl3_Task.R +++ b/R/sl3_Task.R @@ -29,11 +29,11 @@ sl3_Task <- R6Class( class = TRUE, public = list( initialize = function(data, covariates, outcome = NULL, - outcome_type = NULL, outcome_levels = NULL, - id = NULL, weights = NULL, offset = NULL, - nodes = NULL, column_names = NULL, row_index = NULL, - folds = NULL, flag = TRUE, - drop_missing_outcome = FALSE) { + outcome_type = NULL, outcome_levels = NULL, + id = NULL, weights = NULL, offset = NULL, + nodes = NULL, column_names = NULL, row_index = NULL, + folds = NULL, flag = TRUE, + drop_missing_outcome = FALSE) { # generate node list from other arguments if not explicitly specified @@ -199,8 +199,8 @@ sl3_Task <- R6Class( }, next_in_chain = function(covariates = NULL, outcome = NULL, id = NULL, - weights = NULL, offset = NULL, folds = NULL, - column_names = NULL, new_nodes = NULL, ...) { + weights = NULL, offset = NULL, folds = NULL, + column_names = NULL, new_nodes = NULL, ...) { if (is.null(new_nodes)) { new_nodes <- self$nodes @@ -320,7 +320,7 @@ sl3_Task <- R6Class( }, get_node = function(node_name, generator_fun = NULL, - expand_factors = FALSE) { + expand_factors = FALSE) { if (missing(generator_fun)) { generator_fun <- function(node_name, n) { stop(sprintf("Node %s not specified", node_name)) diff --git a/R/utils.R b/R/utils.R index d2e25030..e8c49a22 100644 --- a/R/utils.R +++ b/R/utils.R @@ -142,11 +142,10 @@ reduce_fit_test <- function(learner_fit) { reduced_fit[component] <- NULL reduced$set_train(reduced_fit, task) reduced_predict <- NULL - try( - { - reduced_predict <- reduced$predict() - }, - silent = TRUE + try({ + reduced_predict <- reduced$predict() + }, + silent = TRUE ) if (!identical(original_predict, reduced_predict)) { reduced_fit[component] <- backup diff --git a/man/Custom_chain.Rd b/man/Custom_chain.Rd index aac31b64..201988a4 100644 --- a/man/Custom_chain.Rd +++ b/man/Custom_chain.Rd @@ -7,6 +7,8 @@ \title{Customize chaining for a learner} \format{\code{\link{R6Class}} object.} \usage{ +Custom_chain + customize_chain(learner, chain_fun) } \arguments{ @@ -40,64 +42,44 @@ should be applied.} } \seealso{ -Other Learners: -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Lrnr_HarmonicReg}}, + \code{\link{Lrnr_arima}}, \code{\link{Lrnr_bartMachine}}, + \code{\link{Lrnr_base}}, \code{\link{Lrnr_bilstm}}, + \code{\link{Lrnr_bound}}, \code{\link{Lrnr_caret}}, + \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_HarmonicReg.Rd b/man/Lrnr_HarmonicReg.Rd index d04011a6..9c409a76 100644 --- a/man/Lrnr_HarmonicReg.Rd +++ b/man/Lrnr_HarmonicReg.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_HarmonicReg} \title{Harmonic Regression} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_HarmonicReg +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -28,64 +31,44 @@ forecast of size \code{task$X}.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_arima}}, \code{\link{Lrnr_bartMachine}}, + \code{\link{Lrnr_base}}, \code{\link{Lrnr_bilstm}}, + \code{\link{Lrnr_bound}}, \code{\link{Lrnr_caret}}, + \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_arima.Rd b/man/Lrnr_arima.Rd index c3f63cda..eb02d0da 100644 --- a/man/Lrnr_arima.Rd +++ b/man/Lrnr_arima.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_arima} \title{Univariate ARIMA Models} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_arima +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -30,64 +33,44 @@ forecast of size \code{task$X}.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_bartMachine.Rd b/man/Lrnr_bartMachine.Rd index 861e319b..4a03f1d6 100644 --- a/man/Lrnr_bartMachine.Rd +++ b/man/Lrnr_bartMachine.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_bartMachine} \title{BART Machine Learner} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_bartMachine +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -33,7 +36,7 @@ nonterminal or not.} nonterminal or not.} \item{\code{k}}{For regression, k determines the prior probability that E(Y|X) is contained in the interval (y_{min}, y_{max}), based on a normal -distribution. For example, when k=2, the prior probability is 95\\%. For +distribution. For example, when k=2, the prior probability is 95\%. For classification, k determines the prior probability that E(Y|X) is between (-3,3). Note that a larger value of k results in more shrinkage and a more conservative fit.} @@ -63,64 +66,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_base}}, \code{\link{Lrnr_bilstm}}, + \code{\link{Lrnr_bound}}, \code{\link{Lrnr_caret}}, + \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_base.Rd b/man/Lrnr_base.Rd index 19b111c2..de317cda 100644 --- a/man/Lrnr_base.Rd +++ b/man/Lrnr_base.Rd @@ -7,6 +7,8 @@ \title{Base Class for all sl3 Learners.} \format{\code{\link{R6Class}} object.} \usage{ +Lrnr_base + make_learner(learner_class, ...) } \arguments{ @@ -167,64 +169,44 @@ Throws an error if this learner does not have a \code{fit_object} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_bilstm.Rd b/man/Lrnr_bilstm.Rd index 41d950ed..55441df3 100644 --- a/man/Lrnr_bilstm.Rd +++ b/man/Lrnr_bilstm.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_bilstm} \title{Bidirectional Long short-term memory Recurrent Neural Network (LSTM)} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_bilstm +} \value{ \code{\link{Lrnr_base}} object with methods for training and prediction } @@ -38,64 +41,44 @@ learner. }} \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bound}}, \code{\link{Lrnr_caret}}, + \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_bound.Rd b/man/Lrnr_bound.Rd index 914822b3..ebe9cd92 100644 --- a/man/Lrnr_bound.Rd +++ b/man/Lrnr_bound.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_bound} \title{Bound Predictions} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_bound +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -35,64 +38,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_caret}}, + \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_caret.Rd b/man/Lrnr_caret.Rd index 37d5ce9a..13da8df8 100644 --- a/man/Lrnr_caret.Rd +++ b/man/Lrnr_caret.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_caret} \title{Wrapping Learner for Package Caret} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_caret +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -43,64 +46,44 @@ documentation for \code{\link[caret]{train}}.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_condensier.Rd b/man/Lrnr_condensier.Rd index 4eb831fe..bd04a207 100644 --- a/man/Lrnr_condensier.Rd +++ b/man/Lrnr_condensier.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_condensier} \title{Conditional Density Estimation} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_condensier +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -54,64 +57,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_cv_selector}}, + \code{\link{Lrnr_cv}}, \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_cv.Rd b/man/Lrnr_cv.Rd index ebf80b12..ebb1274d 100644 --- a/man/Lrnr_cv.Rd +++ b/man/Lrnr_cv.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_cv} \title{Fit/Predict a learner with Cross Validation} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_cv +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -25,64 +28,44 @@ This can then be accessed with predict_fold(task, fold_number="full") } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_cv_selector.Rd b/man/Lrnr_cv_selector.Rd index ed3814e3..7bad23f7 100644 --- a/man/Lrnr_cv_selector.Rd +++ b/man/Lrnr_cv_selector.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_cv_selector} \title{Cross-Validated Selector} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_cv_selector +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -37,64 +40,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv}}, \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_dbarts.Rd b/man/Lrnr_dbarts.Rd index b2b045e9..c5856728 100644 --- a/man/Lrnr_dbarts.Rd +++ b/man/Lrnr_dbarts.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_dbarts} \title{Discrete Bayesian Additive Regression Tree sampler} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_dbarts +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -86,6 +89,10 @@ returned in arrays of dimensions equal to \code{nchain} \eqn{\times} \item{\code{keepcall}}{Logical; if \code{FALSE}, returned object will have \code{call} set to \code{call("NULL")}, otherwise the call used to instantiate BART.} +\item{\code{serializeable}}{Logical; if \code{TRUE}, loads the trees into R memory +so the fit object can be saved and loaded. See the section on "Saving" +in \code{\link[dbarts]{bart} NB: This is not currently working} +} } } @@ -103,64 +110,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_define_interactions.Rd b/man/Lrnr_define_interactions.Rd index c54ceca6..bb31d4b1 100644 --- a/man/Lrnr_define_interactions.Rd +++ b/man/Lrnr_define_interactions.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_define_interactions} \title{Define interactions terms} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_define_interactions +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -23,64 +26,43 @@ is already a column with a name matching this given interaction term.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_density_discretize.Rd b/man/Lrnr_density_discretize.Rd index e5344162..eff02ced 100644 --- a/man/Lrnr_density_discretize.Rd +++ b/man/Lrnr_density_discretize.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_density_discretize} \title{Density from Classification} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_density_discretize +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -33,64 +36,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_density_hse.Rd b/man/Lrnr_density_hse.Rd index a9e223a9..0f177364 100644 --- a/man/Lrnr_density_hse.Rd +++ b/man/Lrnr_density_hse.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_density_hse} \title{Density Estimation With Mean Model and Homoscedastic Errors} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_density_hse +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_density_semiparametric.Rd b/man/Lrnr_density_semiparametric.Rd index cf23a8eb..8487e06a 100644 --- a/man/Lrnr_density_semiparametric.Rd +++ b/man/Lrnr_density_semiparametric.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_density_semiparametric} \title{Density Estimation With Mean Model and Homoscedastic Errors} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_density_semiparametric +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, \code{\link{Lrnr_earth}}, + \code{\link{Lrnr_expSmooth}}, \code{\link{Lrnr_gam}}, + \code{\link{Lrnr_gbm}}, \code{\link{Lrnr_glm_fast}}, + \code{\link{Lrnr_glmnet}}, \code{\link{Lrnr_glm}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_earth.Rd b/man/Lrnr_earth.Rd index 7d6328c2..bd557b58 100644 --- a/man/Lrnr_earth.Rd +++ b/man/Lrnr_earth.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_earth} \title{Earth - multivariate adaptive regression splines} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_earth +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -51,64 +54,44 @@ See its documentation for details. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_expSmooth}}, \code{\link{Lrnr_gam}}, + \code{\link{Lrnr_gbm}}, \code{\link{Lrnr_glm_fast}}, + \code{\link{Lrnr_glmnet}}, \code{\link{Lrnr_glm}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_expSmooth.Rd b/man/Lrnr_expSmooth.Rd index 3f3f0bf7..9838af8e 100644 --- a/man/Lrnr_expSmooth.Rd +++ b/man/Lrnr_expSmooth.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_expSmooth} \title{Exponential Smoothing} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_expSmooth +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -62,64 +65,44 @@ forecast of size \code{task$X}.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_gam}}, + \code{\link{Lrnr_gbm}}, \code{\link{Lrnr_glm_fast}}, + \code{\link{Lrnr_glmnet}}, \code{\link{Lrnr_glm}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_gam.Rd b/man/Lrnr_gam.Rd index ec5412c1..3f41e71f 100644 --- a/man/Lrnr_gam.Rd +++ b/man/Lrnr_gam.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_gam} \title{Generalized Additive Models} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_gam +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -52,64 +55,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gbm}}, \code{\link{Lrnr_glm_fast}}, + \code{\link{Lrnr_glmnet}}, \code{\link{Lrnr_glm}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_gbm.Rd b/man/Lrnr_gbm.Rd index 87adcdb0..ebf50599 100644 --- a/man/Lrnr_gbm.Rd +++ b/man/Lrnr_gbm.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_gbm} \title{GBM - generalized boosted regression models} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_gbm +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -38,64 +41,44 @@ See its documentation for details. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_glm_fast}}, + \code{\link{Lrnr_glmnet}}, \code{\link{Lrnr_glm}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_glm.Rd b/man/Lrnr_glm.Rd index 5552449d..0e532b20 100644 --- a/man/Lrnr_glm.Rd +++ b/man/Lrnr_glm.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_glm} \title{Generalized Linear Models} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_glm +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_glm_fast.Rd b/man/Lrnr_glm_fast.Rd index ef43c34f..85e653e8 100644 --- a/man/Lrnr_glm_fast.Rd +++ b/man/Lrnr_glm_fast.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_glm_fast} \title{Computationally Efficient GLMs} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_glm_fast +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -39,64 +42,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glmnet}}, \code{\link{Lrnr_glm}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_glmnet.Rd b/man/Lrnr_glmnet.Rd index 723dc1cf..e6ee31ea 100644 --- a/man/Lrnr_glmnet.Rd +++ b/man/Lrnr_glmnet.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_glmnet} \title{GLMs with Elastic Net Regularization} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_glmnet +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -50,64 +53,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glm}}, + \code{\link{Lrnr_grf}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_grf.Rd b/man/Lrnr_grf.Rd index faec6bb2..ccae3fef 100644 --- a/man/Lrnr_grf.Rd +++ b/man/Lrnr_grf.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_grf} \title{Generalized Random Forests Learner} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_grf +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -76,64 +79,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_h2o_glm.Rd b/man/Lrnr_h2o_glm.Rd index 01318aa3..48a7d9b2 100644 --- a/man/Lrnr_h2o_glm.Rd +++ b/man/Lrnr_h2o_glm.Rd @@ -8,6 +8,8 @@ \format{\code{\link{R6Class}} object.} \usage{ define_h2o_X(task, outcome_type = NULL) + +Lrnr_h2o_glm } \arguments{ \item{task}{An object of type \code{Lrnr_base} as defined in this package.} @@ -60,64 +62,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_h2o_grid.Rd b/man/Lrnr_h2o_grid.Rd index 6636f5f4..f366239e 100644 --- a/man/Lrnr_h2o_grid.Rd +++ b/man/Lrnr_h2o_grid.Rd @@ -7,6 +7,13 @@ \alias{Lrnr_h2o_mutator} \title{Grid Search Models with h2o} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_h2o_grid + +Lrnr_h2o_classifier + +Lrnr_h2o_mutator +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -55,64 +62,45 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} +\keyword{datasets} diff --git a/man/Lrnr_hal9001.Rd b/man/Lrnr_hal9001.Rd index 2af8dd4a..0a1f6db6 100644 --- a/man/Lrnr_hal9001.Rd +++ b/man/Lrnr_hal9001.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_hal9001} \title{The Scalable Highly Adaptive Lasso} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_hal9001 +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -74,64 +77,44 @@ value) using \code{\link[glmnet]{glmnet}} (when set to \code{FALSE}). } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_haldensify.Rd b/man/Lrnr_haldensify.Rd index 0a8dd1ac..7aa2de37 100644 --- a/man/Lrnr_haldensify.Rd +++ b/man/Lrnr_haldensify.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_haldensify} \title{Conditional Density Estimation with the Highly Adaptive LASSO} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_haldensify +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -38,64 +41,43 @@ to be passed to to \code{\link[hal9001]{fit_hal}}. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_independent_binomial.Rd b/man/Lrnr_independent_binomial.Rd index 9ea4bc13..ea379467 100644 --- a/man/Lrnr_independent_binomial.Rd +++ b/man/Lrnr_independent_binomial.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_independent_binomial} \title{Classification from Binomial Regression} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_independent_binomial +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -35,64 +38,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, \code{\link{Lrnr_lstm}}, + \code{\link{Lrnr_mean}}, \code{\link{Lrnr_multivariate}}, + \code{\link{Lrnr_nnls}}, \code{\link{Lrnr_optim}}, + \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_lstm.Rd b/man/Lrnr_lstm.Rd index cc792d30..2f5d8c91 100644 --- a/man/Lrnr_lstm.Rd +++ b/man/Lrnr_lstm.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_lstm} \title{Long short-term memory Recurrent Neural Network (LSTM)} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_lstm +} \value{ \code{\link{Lrnr_base}} object with methods for training and prediction } @@ -38,64 +41,44 @@ learner. }} \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_mean}}, \code{\link{Lrnr_multivariate}}, + \code{\link{Lrnr_nnls}}, \code{\link{Lrnr_optim}}, + \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_mean.Rd b/man/Lrnr_mean.Rd index 77871652..74de348d 100644 --- a/man/Lrnr_mean.Rd +++ b/man/Lrnr_mean.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_mean} \title{Fitting Intercept Models} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_mean +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_multivariate}}, + \code{\link{Lrnr_nnls}}, \code{\link{Lrnr_optim}}, + \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_multivariate.Rd b/man/Lrnr_multivariate.Rd index e40847c1..6408a6cb 100644 --- a/man/Lrnr_multivariate.Rd +++ b/man/Lrnr_multivariate.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_multivariate} \title{Multivariate Learner} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_multivariate +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_nnls}}, \code{\link{Lrnr_optim}}, + \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_nnls.Rd b/man/Lrnr_nnls.Rd index 4ad08066..11beedb7 100644 --- a/man/Lrnr_nnls.Rd +++ b/man/Lrnr_nnls.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_nnls} \title{Non-negative Linear Least Squares} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_nnls +} \value{ Learner object with methods for both training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -38,64 +41,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_optim.Rd b/man/Lrnr_optim.Rd index 46a38973..59f9425c 100644 --- a/man/Lrnr_optim.Rd +++ b/man/Lrnr_optim.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_optim} \title{Optimize Metalearner according to Loss Function using optim} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_optim +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -46,64 +49,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_pca.Rd b/man/Lrnr_pca.Rd index b2105ff8..35b751cc 100644 --- a/man/Lrnr_pca.Rd +++ b/man/Lrnr_pca.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_pca} \title{Principal Component Analysis and Regression} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_pca +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -48,64 +51,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_pkg_condensier_logisfitR6.Rd b/man/Lrnr_pkg_condensier_logisfitR6.Rd index d3b5f0eb..c8e7d6a1 100644 --- a/man/Lrnr_pkg_condensier_logisfitR6.Rd +++ b/man/Lrnr_pkg_condensier_logisfitR6.Rd @@ -4,8 +4,13 @@ \name{Lrnr_pkg_condensier_logisfitR6} \alias{Lrnr_pkg_condensier_logisfitR6} \title{sl3 Learner wrapper for condensier} +\format{An object of class \code{R6ClassGenerator} of length 24.} +\usage{ +Lrnr_pkg_condensier_logisfitR6 +} \description{ This wrapper allows the use of any \code{sl3} Learner as a Learner for \code{condensier}. For details, see the \code{\link[condensier]{fit_density}} function. } +\keyword{datasets} diff --git a/man/Lrnr_polspline.Rd b/man/Lrnr_polspline.Rd index 2fd0f8a3..ce914ea3 100644 --- a/man/Lrnr_polspline.Rd +++ b/man/Lrnr_polspline.Rd @@ -6,6 +6,9 @@ \title{Polyspline - multivariate adaptive polynomial spline regression (polymars) and polychotomous regression and multiple classification (polyclass)} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_polspline +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -31,64 +34,43 @@ See their documentation for details. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_pooled_hazards.Rd b/man/Lrnr_pooled_hazards.Rd index 89f515f6..6554dac4 100644 --- a/man/Lrnr_pooled_hazards.Rd +++ b/man/Lrnr_pooled_hazards.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_pooled_hazards} \title{Classification from Pooled Hazards} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_pooled_hazards +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_randomForest.Rd b/man/Lrnr_randomForest.Rd index 7fc324f2..dd324253 100644 --- a/man/Lrnr_randomForest.Rd +++ b/man/Lrnr_randomForest.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_randomForest} \title{Random Forests} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_randomForest +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -31,64 +34,43 @@ tree.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_ranger.Rd b/man/Lrnr_ranger.Rd index 7cee5347..53e0052b 100644 --- a/man/Lrnr_ranger.Rd +++ b/man/Lrnr_ranger.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_ranger} \title{Ranger - A Fast Implementation of Random Forests} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_ranger +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -28,64 +31,43 @@ See its documentation for details.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_revere_task.Rd b/man/Lrnr_revere_task.Rd index b3288ab3..dc94261e 100644 --- a/man/Lrnr_revere_task.Rd +++ b/man/Lrnr_revere_task.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_revere_task} \title{Learner that chains into a revere task} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_revere_task +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -20,64 +23,43 @@ A wrapper around a revere generator that produces a revere task on chain } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_rfcde.Rd b/man/Lrnr_rfcde.Rd index 620dbb9b..c1f58d12 100644 --- a/man/Lrnr_rfcde.Rd +++ b/man/Lrnr_rfcde.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_rfcde} \title{RFCDE: Random Forests for Conditional Density Estimation} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_rfcde +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -54,64 +57,44 @@ Consult the documentation of that package for details. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rpart}}, + \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_rpart.Rd b/man/Lrnr_rpart.Rd index bcac3b7e..124d9ac5 100644 --- a/man/Lrnr_rpart.Rd +++ b/man/Lrnr_rpart.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_rpart} \title{Learner for Recursive Partitioning and Regression Trees.} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_rpart +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -31,64 +34,44 @@ result. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_rugarch.Rd b/man/Lrnr_rugarch.Rd index ed5b2887..b957e1c4 100644 --- a/man/Lrnr_rugarch.Rd +++ b/man/Lrnr_rugarch.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_rugarch} \title{Univariate GARCH Models} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_rugarch +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -35,64 +38,44 @@ fixed during the optimization.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_screener_corP.Rd b/man/Lrnr_screener_corP.Rd index 7712acd9..27d22d53 100644 --- a/man/Lrnr_screener_corP.Rd +++ b/man/Lrnr_screener_corP.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_screener_corP} \title{Correlation P-value Screener} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_screener_corP +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -24,64 +27,43 @@ from a test of correlation provided by the \code{stats} package, } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_screener_corRank.Rd b/man/Lrnr_screener_corRank.Rd index 10c98afd..1d7d61dd 100644 --- a/man/Lrnr_screener_corRank.Rd +++ b/man/Lrnr_screener_corRank.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_screener_corRank} \title{Correlation Rank Screener} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_screener_corRank +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -23,64 +26,43 @@ by the p-values returned from a test of correlation provided by the } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_screener_randomForest.Rd b/man/Lrnr_screener_randomForest.Rd index ae51a609..56e297d2 100644 --- a/man/Lrnr_screener_randomForest.Rd +++ b/man/Lrnr_screener_randomForest.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_screener_randomForest} \title{Random Forest Screener} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_screener_randomForest +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -26,64 +29,43 @@ function. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_sl.Rd b/man/Lrnr_sl.Rd index dbeeb2a7..9e32e434 100644 --- a/man/Lrnr_sl.Rd +++ b/man/Lrnr_sl.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_sl} \title{SuperLearner Algorithm} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_sl +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -45,64 +48,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_solnp.Rd b/man/Lrnr_solnp.Rd index 352d8f40..a62e4588 100644 --- a/man/Lrnr_solnp.Rd +++ b/man/Lrnr_solnp.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_solnp} \title{Nonlinear Optimization via Augmented Lagrange} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_solnp +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -49,64 +52,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_solnp_density.Rd b/man/Lrnr_solnp_density.Rd index 1b104073..658df234 100644 --- a/man/Lrnr_solnp_density.Rd +++ b/man/Lrnr_solnp_density.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_solnp_density} \title{Nonlinear Optimization via Augmented Lagrange} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_solnp_density +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -38,64 +41,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp}}, + \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_stratified.Rd b/man/Lrnr_stratified.Rd index 07cba31f..b6234f60 100644 --- a/man/Lrnr_stratified.Rd +++ b/man/Lrnr_stratified.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_stratified} \title{Stratify learner fits by a single variable} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_stratified +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -28,64 +31,44 @@ variables with discrete levels coded as \code{numeric}. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_subset_covariates.Rd b/man/Lrnr_subset_covariates.Rd index a4adba74..ea5fd88e 100644 --- a/man/Lrnr_subset_covariates.Rd +++ b/man/Lrnr_subset_covariates.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_subset_covariates} \title{Learner with Covariate Subsetting} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_subset_covariates +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,43 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_svm.Rd b/man/Lrnr_svm.Rd index 5a7aa3c3..60e93ac6 100644 --- a/man/Lrnr_svm.Rd +++ b/man/Lrnr_svm.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_svm} \title{Support Vector Machines} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_svm +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -41,64 +44,44 @@ See its documentation for details.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_tsDyn}}, \code{\link{Lrnr_xgboost}}, + \code{\link{Pipeline}}, \code{\link{Stack}}, + \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_tsDyn.Rd b/man/Lrnr_tsDyn.Rd index 877e7904..890b33ee 100644 --- a/man/Lrnr_tsDyn.Rd +++ b/man/Lrnr_tsDyn.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_tsDyn} \title{Nonlinear Time Series Analysis} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_tsDyn +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -75,64 +78,44 @@ relation.} } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_xgboost}}, + \code{\link{Pipeline}}, \code{\link{Stack}}, + \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Lrnr_xgboost.Rd b/man/Lrnr_xgboost.Rd index 921410c6..2528d5f1 100644 --- a/man/Lrnr_xgboost.Rd +++ b/man/Lrnr_xgboost.Rd @@ -5,6 +5,9 @@ \alias{Lrnr_xgboost} \title{xgboost: eXtreme Gradient Boosting} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_xgboost +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -39,64 +42,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Pipeline}}, \code{\link{Stack}}, + \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Pipeline.Rd b/man/Pipeline.Rd index 4e0cf811..013c63ef 100644 --- a/man/Pipeline.Rd +++ b/man/Pipeline.Rd @@ -5,6 +5,9 @@ \alias{Pipeline} \title{Pipeline (chain) of learners.} \format{\code{\link{R6Class}} object.} +\usage{ +Pipeline +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -41,64 +44,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Stack}}, + \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/Shared_Data.Rd b/man/Shared_Data.Rd index cf4748c8..123c2b75 100644 --- a/man/Shared_Data.Rd +++ b/man/Shared_Data.Rd @@ -1,8 +1,14 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/Shared_Data.R +\docType{data} \name{Shared_Data} \alias{Shared_Data} \title{Container Class for data.table Shared Between Tasks} +\format{An object of class \code{R6ClassGenerator} of length 24.} +\usage{ +Shared_Data +} \description{ Mostly to deal with alloc.col shallow copies, but also nice to have a bit more abstraction. } +\keyword{datasets} diff --git a/man/Stack.Rd b/man/Stack.Rd index 94139d95..d79a416f 100644 --- a/man/Stack.Rd +++ b/man/Stack.Rd @@ -5,6 +5,9 @@ \alias{Stack} \title{Learner Stacking} \format{\code{\link{R6Class}} object.} +\usage{ +Stack +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -34,64 +37,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} diff --git a/man/SuperLearner_interface.Rd b/man/SuperLearner_interface.Rd index 8d599e0e..b43c6524 100644 --- a/man/SuperLearner_interface.Rd +++ b/man/SuperLearner_interface.Rd @@ -8,6 +8,13 @@ \alias{Lrnr_pkg_SuperLearner_screener} \title{Use SuperLearner Wrappers, Screeners, and Methods, in sl3} \format{\code{\link{R6Class}} object.} +\usage{ +Lrnr_pkg_SuperLearner + +Lrnr_pkg_SuperLearner_method + +Lrnr_pkg_SuperLearner_screener +} \value{ Learner object with methods for training and prediction. See \code{\link{Lrnr_base}} for documentation on learners. @@ -47,64 +54,44 @@ by all learners. } \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()}, -\code{\link{undocumented_learner}} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}}, + \code{\link{undocumented_learner}} } \concept{Learners} \keyword{data} +\keyword{datasets} diff --git a/man/cpp.Rd b/man/cpp.Rd index b650f4a2..9826926a 100644 --- a/man/cpp.Rd +++ b/man/cpp.Rd @@ -51,8 +51,6 @@ of longitudinal research 1 (1984): 185-227. } \usage{ data(cpp) - -data(cpp_imputed) } \description{ Subset of growth data from the collaborative perinatal project (CPP). diff --git a/man/learner_helpers.Rd b/man/learner_helpers.Rd index 603ea22f..2dd3a69d 100644 --- a/man/learner_helpers.Rd +++ b/man/learner_helpers.Rd @@ -16,7 +16,7 @@ delayed_make_learner(learner_class, ...) learner_train(learner, task, trained_sublearners) -delayed_learner_train(learner, task) +delayed_learner_train(learner, task, name = NULL) learner_fit_predict(learner_fit, task = NULL) @@ -42,6 +42,8 @@ delayed_learner_subset_covariates(learner, task) \item{trained_sublearners}{Any data obtained from a \code{train_sublearners} step.} +\item{name}{a more detailed name for this delayed task, if necessary} + \item{learner_fit}{a learner object that has already been fit} } \description{ diff --git a/man/sl3_Task.Rd b/man/sl3_Task.Rd index f08e05f4..22f85711 100644 --- a/man/sl3_Task.Rd +++ b/man/sl3_Task.Rd @@ -7,6 +7,8 @@ \title{Define a Machine Learning Task} \format{\code{\link{R6Class}} object.} \usage{ +sl3_Task + make_sl3_Task(...) } \arguments{ diff --git a/man/sl3_revere_Task.Rd b/man/sl3_revere_Task.Rd index 68589a62..6c57bc6e 100644 --- a/man/sl3_revere_Task.Rd +++ b/man/sl3_revere_Task.Rd @@ -4,6 +4,10 @@ \name{sl3_revere_Task} \alias{sl3_revere_Task} \title{Revere (SplitSpecific) Task} +\format{An object of class \code{R6ClassGenerator} of length 24.} +\usage{ +sl3_revere_Task +} \description{ A task that has different realizations in different folds Useful for Revere CV operations diff --git a/man/undocumented_learner.Rd b/man/undocumented_learner.Rd index a5ab8c30..36fa04bf 100644 --- a/man/undocumented_learner.Rd +++ b/man/undocumented_learner.Rd @@ -20,64 +20,43 @@ includes things like model hyperparameters.} }} \seealso{ -Other Learners: -\code{\link{Custom_chain}}, -\code{\link{Lrnr_HarmonicReg}}, -\code{\link{Lrnr_arima}}, -\code{\link{Lrnr_bartMachine}}, -\code{\link{Lrnr_base}}, -\code{\link{Lrnr_bilstm}}, -\code{\link{Lrnr_bound}}, -\code{\link{Lrnr_caret}}, -\code{\link{Lrnr_condensier}}, -\code{\link{Lrnr_cv_selector}}, -\code{\link{Lrnr_cv}}, -\code{\link{Lrnr_dbarts}}, -\code{\link{Lrnr_define_interactions}}, -\code{\link{Lrnr_density_discretize}}, -\code{\link{Lrnr_density_hse}}, -\code{\link{Lrnr_density_semiparametric}}, -\code{\link{Lrnr_earth}}, -\code{\link{Lrnr_expSmooth}}, -\code{\link{Lrnr_gam}}, -\code{\link{Lrnr_gbm}}, -\code{\link{Lrnr_glm_fast}}, -\code{\link{Lrnr_glmnet}}, -\code{\link{Lrnr_glm}}, -\code{\link{Lrnr_grf}}, -\code{\link{Lrnr_h2o_grid}}, -\code{\link{Lrnr_hal9001}}, -\code{\link{Lrnr_haldensify}}, -\code{\link{Lrnr_independent_binomial}}, -\code{\link{Lrnr_lstm}}, -\code{\link{Lrnr_mean}}, -\code{\link{Lrnr_multivariate}}, -\code{\link{Lrnr_nnls}}, -\code{\link{Lrnr_optim}}, -\code{\link{Lrnr_pca}}, -\code{\link{Lrnr_pkg_SuperLearner}}, -\code{\link{Lrnr_polspline}}, -\code{\link{Lrnr_pooled_hazards}}, -\code{\link{Lrnr_randomForest}}, -\code{\link{Lrnr_ranger}}, -\code{\link{Lrnr_revere_task}}, -\code{\link{Lrnr_rfcde}}, -\code{\link{Lrnr_rpart}}, -\code{\link{Lrnr_rugarch}}, -\code{\link{Lrnr_screener_corP}}, -\code{\link{Lrnr_screener_corRank}}, -\code{\link{Lrnr_screener_randomForest}}, -\code{\link{Lrnr_sl}}, -\code{\link{Lrnr_solnp_density}}, -\code{\link{Lrnr_solnp}}, -\code{\link{Lrnr_stratified}}, -\code{\link{Lrnr_subset_covariates}}, -\code{\link{Lrnr_svm}}, -\code{\link{Lrnr_tsDyn}}, -\code{\link{Lrnr_xgboost}}, -\code{\link{Pipeline}}, -\code{\link{Stack}}, -\code{\link{define_h2o_X}()} +Other Learners: \code{\link{Custom_chain}}, + \code{\link{Lrnr_HarmonicReg}}, \code{\link{Lrnr_arima}}, + \code{\link{Lrnr_bartMachine}}, \code{\link{Lrnr_base}}, + \code{\link{Lrnr_bilstm}}, \code{\link{Lrnr_bound}}, + \code{\link{Lrnr_caret}}, \code{\link{Lrnr_condensier}}, + \code{\link{Lrnr_cv_selector}}, \code{\link{Lrnr_cv}}, + \code{\link{Lrnr_dbarts}}, + \code{\link{Lrnr_define_interactions}}, + \code{\link{Lrnr_density_discretize}}, + \code{\link{Lrnr_density_hse}}, + \code{\link{Lrnr_density_semiparametric}}, + \code{\link{Lrnr_earth}}, \code{\link{Lrnr_expSmooth}}, + \code{\link{Lrnr_gam}}, \code{\link{Lrnr_gbm}}, + \code{\link{Lrnr_glm_fast}}, \code{\link{Lrnr_glmnet}}, + \code{\link{Lrnr_glm}}, \code{\link{Lrnr_grf}}, + \code{\link{Lrnr_h2o_grid}}, \code{\link{Lrnr_hal9001}}, + \code{\link{Lrnr_haldensify}}, + \code{\link{Lrnr_independent_binomial}}, + \code{\link{Lrnr_lstm}}, \code{\link{Lrnr_mean}}, + \code{\link{Lrnr_multivariate}}, \code{\link{Lrnr_nnls}}, + \code{\link{Lrnr_optim}}, \code{\link{Lrnr_pca}}, + \code{\link{Lrnr_pkg_SuperLearner}}, + \code{\link{Lrnr_polspline}}, + \code{\link{Lrnr_pooled_hazards}}, + \code{\link{Lrnr_randomForest}}, + \code{\link{Lrnr_ranger}}, + \code{\link{Lrnr_revere_task}}, \code{\link{Lrnr_rfcde}}, + \code{\link{Lrnr_rpart}}, \code{\link{Lrnr_rugarch}}, + \code{\link{Lrnr_screener_corP}}, + \code{\link{Lrnr_screener_corRank}}, + \code{\link{Lrnr_screener_randomForest}}, + \code{\link{Lrnr_sl}}, \code{\link{Lrnr_solnp_density}}, + \code{\link{Lrnr_solnp}}, \code{\link{Lrnr_stratified}}, + \code{\link{Lrnr_subset_covariates}}, + \code{\link{Lrnr_svm}}, \code{\link{Lrnr_tsDyn}}, + \code{\link{Lrnr_xgboost}}, \code{\link{Pipeline}}, + \code{\link{Stack}}, \code{\link{define_h2o_X}} } \concept{Learners} \keyword{data} diff --git a/man/variable_type.Rd b/man/variable_type.Rd index 0cfd703c..666e2aba 100644 --- a/man/variable_type.Rd +++ b/man/variable_type.Rd @@ -1,17 +1,16 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/Variable_Type.R +\docType{data} \name{Variable_Type} \alias{Variable_Type} \alias{variable_type} \title{Specify variable type} +\format{An object of class \code{R6ClassGenerator} of length 24.} \usage{ -variable_type( - type = NULL, - levels = NULL, - bounds = NULL, - x = NULL, - pcontinuous = getOption("sl3.pcontinuous") -) +Variable_Type + +variable_type(type = NULL, levels = NULL, bounds = NULL, x = NULL, + pcontinuous = getOption("sl3.pcontinuous")) } \arguments{ \item{type}{A type name.} @@ -28,3 +27,4 @@ observations above which variable is continuous} \description{ Specify variable type } +\keyword{datasets} diff --git a/tests/testthat/test-barts.R b/tests/testthat/test-barts.R index 34105382..76a8f6d9 100644 --- a/tests/testthat/test-barts.R +++ b/tests/testthat/test-barts.R @@ -79,3 +79,27 @@ test_that("Lrnr_dbarts with binary outcome works", { mean_pred_sl3 <- mean(dbart_fit$predict(task)) expect_true(mean_pred_sl3 < 20) }) + + +# test_that("Lrnr_dbarts can be serialized with appropriate param", { +# dbart_learner_serializable <- Lrnr_dbarts$new(serializeable=TRUE) +# dbarts_s_fit <- dbart_learner_serializable$train(task) +# +# preds <- dbarts_s_fit$predict() +# tmp <- tempfile() +# save(dbarts_s_fit, file=tmp) +# rm(dbarts_s_fit) +# load(tmp) +# preds_from_serialized <- dbarts_s_fit$predict() +# tmp <- tempfile() +# +# db_fit <- dbarts_s_fit$fit_object +# z <- db_fit$fit$storeState() +# invisible(db_fit$fit$state) +# predict(db_fit, as.matrix(task$X)) +# save(db_fit, file=tmp) +# rm(db_fit) +# load(tmp) +# predict(db_fit, as.matrix(task$X)) +# expect_equal(preds, preds_from_serialized) +# }) diff --git a/tests/testthat/test-rpart.R b/tests/testthat/test-rpart.R index 72a9e1e2..8df7e8bb 100644 --- a/tests/testthat/test-rpart.R +++ b/tests/testthat/test-rpart.R @@ -70,3 +70,23 @@ test_that("Lrnr_rpart predictions match those from rpart", { ## test equivalence of prediction from Lrnr_rpart and rpart::rpart expect_equal(prd_lrnr_rpart, prd_rpart) }) + +# try to reproduce https://github.com/tlverse/sl3/issues/230 +library(sl3) +library(testthat) +library(rpart) + +# define test dataset +data(mtcars) +task <- sl3_Task$new(mtcars, covariates = c( + "cyl", "disp", "hp", "drat", "wt", "qsec", + "vs", "am", "gear", "carb" +), outcome = "mpg") + + +lrnr_rpart <- Lrnr_rpart$new() +lrnr_mean <- Lrnr_mean$new() +stack <- Stack$new(lrnr_rpart, lrnr_mean) + +stack_fit <- stack$train(task) +predict <- stack_fit$predict() diff --git a/tests/testthat/test-sl.R b/tests/testthat/test-sl.R index 4ab942bd..d725a764 100644 --- a/tests/testthat/test-sl.R +++ b/tests/testthat/test-sl.R @@ -17,10 +17,12 @@ glmnet_learner <- Lrnr_pkg_SuperLearner$new("SL.glmnet") subset_apgar <- Lrnr_subset_covariates$new(covariates = c("apgar1", "apgar5")) learners <- list(glm_learner, glmnet_learner, subset_apgar) sl1 <- make_learner(Lrnr_sl, learners, glm_learner) -# sl3_debug_mode() -# debugonce(sl1$.__enclos_env__$private$.train) -# debugonce(sl1$.__enclos_env__$private$.train_sublearners) + sl1_fit <- sl1$train(task) +test_that("Coefficients can extracted from sl fits", expect_true(!is.null(coef(sl1_fit)))) +glm_fit <- sl1_fit$learner_fits$Lrnr_glm_TRUE +test_that("Library fits can extracted from sl fits", expect_true(inherits(glm_fit, "Lrnr_glm"))) + sl1_risk <- sl1_fit$cv_risk(loss_squared_error) @@ -47,3 +49,20 @@ expect_lt(length(sl1_small_fit$fit_object), length(sl1_fit$fit_object)) preds <- sl1_small_fit$predict(task) preds_fold <- sl1_small_fit$predict_fold(task, "full") test_that("predict_fold(task,'full') works if keep_extra=FALSE", expect_equal(preds, preds_fold)) + +# sl of a pipeline from https://github.com/tlverse/sl3/issues/81 +data(cpp) +cpp <- cpp[!is.na(cpp[, "haz"]), ] +covars <- c("apgar1", "apgar5", "parity", "gagebrth", "mage", "meducyrs", "sexn") +cpp[is.na(cpp)] <- 0 +outcome <- "haz" +task <- sl3_Task$new(cpp, covariates = covars, outcome = outcome) +make_inter <- Lrnr_define_interactions$new(interactions = list(c("apgar1", "parity"), c("apgar5", "parity"))) + +glm_learner <- Lrnr_glm$new() +glmnet_learner <- Lrnr_glmnet$new(nlambda = 5) +learners <- Stack$new(glm_learner, glmnet_learner) +pipe <- Pipeline$new(make_inter, learners) +sl1 <- make_learner(Lrnr_sl, pipe, metalearner = Lrnr_solnp$new()) +fit <- sl1$train(task) +print(fit) diff --git a/tests/testthat/test-stack.R b/tests/testthat/test-stack.R index bf03b99e..6a548b69 100644 --- a/tests/testthat/test-stack.R +++ b/tests/testthat/test-stack.R @@ -37,3 +37,8 @@ stack_lrnr_names <- as.character(stack_dens$print()) test_that("Repetitive names of learners in stack differ after creation", { expect_false(stack_lrnr_names[1] == stack_lrnr_names[2]) }) + +# check that you can create a stack of one learner +stack_one <- Stack$new(glm_learner) +fit <- stack_one$train(task) +preds <- fit$predict(task)