Set one attribute of a lgb.Dataset
set_field(dataset, field_name, data)
# S3 method for lgb.Dataset
set_field(dataset, field_name, data)Object of class lgb.Dataset
String with the name of the attribute to set. One of the following.
label: label lightgbm learns from ;
weight: to do a weight rescale ;
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 100-document dataset with group = c(10, 20, 40, 10, 10, 10),
that means that you have 6 groups, where the first 10 records are in the first group,
records 11-30 are in the second group, etc.
init_score: initial score is the base prediction lightgbm will boost from.
The data for the field. See examples.
The lgb.Dataset you passed in.
# \donttest{
setLGBMthreads(2L)
data.table::setDTthreads(1L)
data(agaricus.train, package = "lightgbm")
train <- agaricus.train
dtrain <- lgb.Dataset(train$data, label = train$label)
lgb.Dataset.construct(dtrain)
labels <- lightgbm::get_field(dtrain, "label")
lightgbm::set_field(dtrain, "label", 1 - labels)
labels2 <- lightgbm::get_field(dtrain, "label")
stopifnot(all.equal(labels2, 1 - labels))
# }