Set one attribute of a lgb.Dataset

setinfo(dataset, ...)

# S3 method for lgb.Dataset
setinfo(dataset, name, info, ...)

Arguments

dataset

Object of class lgb.Dataset

...

other parameters (ignored)

name

the name of the field to get

info

the specific field of information to set

Value

the dataset you passed in

Details

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 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.

Examples

# \donttest{
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")
#> Warning: Calling getinfo() on a lgb.Dataset is deprecated. Use get_field() instead.
lightgbm::setinfo(dtrain, "label", 1 - labels)
#> Warning: Calling setinfo() on a lgb.Dataset is deprecated. Use set_field() instead.

labels2 <- lightgbm::getinfo(dtrain, "label")
#> Warning: Calling getinfo() on a lgb.Dataset is deprecated. Use get_field() instead.
stopifnot(all.equal(labels2, 1 - labels))
# }