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NAMESPACE
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NAMESPACE
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## we use S4
import("methods")
importFrom("graphics", "plot", "barplot", "lines", "text") ## we need the generic for plot
importFrom("utils", "head")
importFrom("stats", "sd", "median", "princomp", "loadings", "runif",
"rnorm", "cor")
importFrom("registry", "registry", "match_partial_ignorecase", "match_exact")
importFrom("proxy", "dist", "as.dist")
## get generics, cladses and methods
importClassesFrom("Matrix", "Matrix", "dsparseMatrix", "dgCMatrix", "ngCMatrix", "dgTMatrix")
importFrom("Matrix", "rowSums", "colSums", "rowMeans", "colMeans",
"summary", "drop0", "rBind")
## get just methods
importMethodsFrom("Matrix", "image", "t", "crossprod", "tcrossprod", "which")
importFrom("matrixStats", "colMaxs", "colMins")
## get generics and methods
importFrom("arules", "predict", "nitems", "sample", "LIST",
"dissimilarity", "apriori", "itemLabels", "encode")
## get just methods
importMethodsFrom("arules", "sort", "summary",
"lhs", "rhs", "quality", "quality<-", "is.subset", "interestMeasure")
### truncated SVD
importFrom("irlba", "irlba")
### LIBMF
importFrom("recosystem", "Reco", "data_memory", "out_memory")
## export functions
export(
"dropNA",
"dropNA2matrix",
"dropNAis.na",
"funkSVD",
"RMSE",
"MSE",
"MAE",
"frobenius",
"HybridRecommender",
"returnRatings",
"getParameters"
)
## registry uses S3
export("recommenderRegistry")
S3method("print", "recommender_method")
## recommenderlab exports
exportClasses(
# "sparseNAMatrix",
"ratingMatrix",
"realRatingMatrix",
"binaryRatingMatrix",
"Recommender",
"topNList",
"evaluationScheme",
"confusionMatrix",
"evaluationResults",
"evaluationResultList"
)
S3method("predict", "funkSVD")
exportMethods(
"[",
"c",
"coerce", ## setAs
"show",
"plot",
"image",
"sample",
"summary",
"calcPredictionAccuracy",
"predict",
# "colMeans",
# "rowMeans",
"colCounts",
"rowCounts",
"colSds",
"rowSds",
"binarize",
"avg",
"evaluate",
"bestN",
"nratings",
"normalize",
"denormalize",
"getNormalize",
"getRatings",
"getRatingMatrix",
"getRuns",
"getModel",
"getData",
"getConfusionMatrix",
"getResults",
"getTopNLists",
"hasRating",
"dissimilarity",
"similarity",
"evaluationScheme",
"removeKnownRatings",
"removeKnownItems",
"Recommender",
"getList",
"getData.frame"
)