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[R] add reset_data in lgb.cv #1874

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Dec 1, 2018
Merged

[R] add reset_data in lgb.cv #1874

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6d08b9f
add free booster in lgb.cv
guolinke Nov 25, 2018
9b88655
change to reset_data
guolinke Nov 25, 2018
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16 changes: 15 additions & 1 deletion R-package/R/lgb.cv.R
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,7 @@ CVBooster <- R6::R6Class(
#' type str represents feature names
#' @param callbacks list of callback functions
#' 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"}}
Expand Down Expand Up @@ -87,6 +88,7 @@ lgb.cv <- function(params = list(),
categorical_feature = NULL,
early_stopping_rounds = NULL,
callbacks = list(),
reset_data = FALSE,
...) {

# Setup temporary variables
Expand Down Expand Up @@ -303,7 +305,19 @@ lgb.cv <- function(params = list(),
if (env$met_early_stop) break

}

if (reset_data) {
lapply(cv_booster$boosters, function(fd) {
# Store temporarily model data elsewhere
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Makes sense to me

booster_old <- list(best_iter = fd$booster$best_iter,
best_score = fd$booster$best_score,
record_evals = fd$booster$record_evals)
# Reload model
fd$booster <- lgb.load(model_str = fd$booster$save_model_to_string())
fd$booster$best_iter <- booster_old$best_iter
fd$booster$best_score <- booster_old$best_score
fd$booster$record_evals <- booster_old$record_evals
})
}
# Return booster
return(cv_booster)

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2 changes: 2 additions & 0 deletions R-package/R/lgb.train.R
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Expand Up @@ -12,6 +12,8 @@
#' @param categorical_feature list of str or int
#' type int represents index,
#' type str represents feature names
#' @param callbacks list of callback functions
#' List of callback functions that are applied at each iteration.
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how is this change related?

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I find the doc of this parameter is misning, compared with lgb.cv.

#' @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{
Expand Down