% Generated by roxygen2: do not edit by hand % Please edit documentation in R/lgb.Dataset.R \name{set_field} \alias{set_field} \alias{set_field.lgb.Dataset} \title{Set one attribute of a \code{lgb.Dataset} object} \usage{ set_field(dataset, field_name, data) \method{set_field}{lgb.Dataset}(dataset, field_name, data) } \arguments{ \item{dataset}{Object of class \code{lgb.Dataset}} \item{field_name}{String with the name of the attribute to set. One of the following. \itemize{ \item \code{label}: label lightgbm learns from ; \item \code{weight}: to do a weight rescale ; \item{\code{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 \code{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.} \item \code{init_score}: initial score is the base prediction lightgbm will boost from. }} \item{data}{The data for the field. See examples.} } \value{ The \code{lgb.Dataset} you passed in. } \description{ Set one attribute of a \code{lgb.Dataset} } \examples{ \donttest{ \dontshow{setLGBMthreads(2L)} \dontshow{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)) } }