stop("lgb.self.get.handle: supplied a too large value in categorical_feature: ",max(private$categorical_feature)," but only ",length(private$colnames)," features")
stop(
"lgb.self.get.handle: supplied a too large value in categorical_feature: "
,max(private$categorical_feature)
," but only "
,length(private$colnames)
," features"
)
}
# Store indices as [0, n-1] indexed instead of [1, n] indexed
#' List of callback functions that are applied at each iteration.
#' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the booster model into a predictor model which frees up memory and the original datasets
#' @param callbacks List of callback functions that are applied at each iteration.
#' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the booster model
#' into a predictor model which frees up memory and the original datasets
#' @param ... other parameters, see Parameters.rst for more information. A few key parameters:
#' \itemize{
#' \item{boosting}{Boosting type. \code{"gbdt"} or \code{"dart"}}
#' Data preparator for LightGBM datasets (numeric)
#'
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}. Factors and characters are converted to numeric without integers. Please use \code{lgb.prepare_rules} if you want to apply this transformation to other datasets.
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}.
#' Factors and characters are converted to numeric without integers. Please use
#' \code{lgb.prepare_rules} if you want to apply this transformation to other datasets.
#'
#' @param data A data.frame or data.table to prepare.
#'
#' @return The cleaned dataset. It must be converted to a matrix format (\code{as.matrix}) for input in \code{lgb.Dataset}.
#' @return The cleaned dataset. It must be converted to a matrix format (\code{as.matrix})
#' Data preparator for LightGBM datasets (integer)
#'
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}. Factors and characters are converted to numeric (specifically: integer). Please use \code{lgb.prepare_rules2} if you want to apply this transformation to other datasets. This is useful if you have a specific need for integer dataset instead of numeric dataset. Note that there are programs which do not support integer-only input. Consider this as a half memory technique which is dangerous, especially for LightGBM.
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}.
#' Factors and characters are converted to numeric (specifically: integer).
#' Please use \code{lgb.prepare_rules2} if you want to apply this transformation to other datasets.
#' This is useful if you have a specific need for integer dataset instead of numeric dataset.
#' Note that there are programs which do not support integer-only input. Consider this as a half
#' memory technique which is dangerous, especially for LightGBM.
#'
#' @param data A data.frame or data.table to prepare.
#'
#' @return The cleaned dataset. It must be converted to a matrix format (\code{as.matrix}) for input in \code{lgb.Dataset}.
#' @return The cleaned dataset. It must be converted to a matrix format (\code{as.matrix})
#' Data preparator for LightGBM datasets with rules (numeric)
#'
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}. Factors and characters are converted to numeric. In addition, keeps rules created so you can convert other datasets using this converter.
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}.
#' Factors and characters are converted to numeric. In addition, keeps rules created
#' so you can convert other datasets using this converter.
#'
#' @param data A data.frame or data.table to prepare.
#' @param rules A set of rules from the data preparator, if already used.
#'
#' @return A list with the cleaned dataset (\code{data}) and the rules (\code{rules}). The data must be converted to a matrix format (\code{as.matrix}) for input in \code{lgb.Dataset}.
#' @return A list with the cleaned dataset (\code{data}) and the rules (\code{rules}).
#' The data must be converted to a matrix format (\code{as.matrix}) for input
#' Data preparator for LightGBM datasets with rules (integer)
#'
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}. Factors and characters are converted to numeric (specifically: integer). In addition, keeps rules created so you can convert other datasets using this converter. This is useful if you have a specific need for integer dataset instead of numeric dataset. Note that there are programs which do not support integer-only input. Consider this as a half memory technique which is dangerous, especially for LightGBM.
#' Attempts to prepare a clean dataset to prepare to put in a \code{lgb.Dataset}.
#' Factors and characters are converted to numeric (specifically: integer).
#' In addition, keeps rules created so you can convert other datasets using this converter.
#' This is useful if you have a specific need for integer dataset instead of numeric dataset.
#' Note that there are programs which do not support integer-only input.
#' Consider this as a half memory technique which is dangerous, especially for LightGBM.
#'
#' @param data A data.frame or data.table to prepare.
#' @param rules A set of rules from the data preparator, if already used.
#'
#' @return A list with the cleaned dataset (\code{data}) and the rules (\code{rules}). The data must be converted to a matrix format (\code{as.matrix}) for input in \code{lgb.Dataset}.
#' @return A list with the cleaned dataset (\code{data}) and the rules (\code{rules}).
#' The data must be converted to a matrix format (\code{as.matrix}) for input in
#' List of callback functions that are applied at each iteration.
#' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the booster model into a predictor model which frees up memory and the original datasets
#' @param callbacks List of callback functions that are applied at each iteration.
#' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the
#' booster model into a predictor model which frees up memory and the
#' original datasets
#' @param ... other parameters, see Parameters.rst for more information. A few key parameters:
#' \itemize{
#' \item{boosting}{Boosting type. \code{"gbdt"} or \code{"dart"}}
#' Attempts to unload LightGBM packages so you can remove objects cleanly without having to restart R. This is useful for instance if an object becomes stuck for no apparent reason and you do not want to restart R to fix the lost object.
#'
#' @param restore Whether to reload \code{LightGBM} immediately after detaching from R. Defaults to \code{TRUE} which means automatically reload \code{LightGBM} once unloading is performed.
#' @param wipe Whether to wipe all \code{lgb.Dataset} and \code{lgb.Booster} from the global environment. Defaults to \code{FALSE} which means to not remove them.
#' @param envir The environment to perform wiping on if \code{wipe == TRUE}. Defaults to \code{.GlobalEnv} which is the global environment.
#' @param restore Whether to reload \code{LightGBM} immediately after detaching from R.
#' Defaults to \code{TRUE} which means automatically reload \code{LightGBM} once
#' unloading is performed.
#' @param wipe Whether to wipe all \code{lgb.Dataset} and \code{lgb.Booster} from the global
#' environment. Defaults to \code{FALSE} which means to not remove them.
#' @param envir The environment to perform wiping on if \code{wipe == TRUE}. Defaults to
#' \code{.GlobalEnv} which is the global environment.
