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) the name of the field to get 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))
# }