Set one attribute of a lgb.Dataset
setinfo(dataset, ...) # S3 method for lgb.Dataset setinfo(dataset, name, info, ...)
dataset | Object of class |
---|---|
... | other parameters |
name | the name of the field to get |
info | the specific field of information to set |
passed object
The name
field can be one of the following:
label
: vector of labels to use as the target variable
weight
: to do a weight rescale
init_score
: initial score is the base prediction lightgbm will boost from
group
: used for learning-to-rank tasks. An integer vector describing how to
group rows together as ordered results from the same set of candidate results to be ranked.
For example, if you have a 1000-row dataset that contains 250 4-document query results,
set this to rep(4L, 250L)
# \dontrun{ data(agaricus.train, package = "lightgbm") train <- agaricus.train dtrain <- lgb.Dataset(train$data, label = train$label) lgb.Dataset.construct(dtrain) labels <- lightgbm::getinfo(dtrain, "label") lightgbm::setinfo(dtrain, "label", 1 - labels) labels2 <- lightgbm::getinfo(dtrain, "label") stopifnot(all.equal(labels2, 1 - labels)) # }