Set one attribute of a lgb.Dataset

setinfo(dataset, ...)

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



Object of class lgb.Dataset


other parameters


the name of the field to get


the specific field of information to set


the dataset you passed in

the dataset you passed in


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)


# \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") lightgbm::setinfo(dtrain, "label", 1 - labels) labels2 <- lightgbm::getinfo(dtrain, "label") stopifnot(all.equal(labels2, 1 - labels)) # }