Alien-XGBoost
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xgboost/R-package/R/callbacks.R view on Meta::CPAN
if (is.null(mnames))
init(env)
if (finalize)
return(finalizer(env))
ev <- env$bst_evaluation
if(!is.null(env$bst_evaluation_err))
ev <- c(ev, env$bst_evaluation_err)
env$evaluation_log <- c(env$evaluation_log,
list(c(iter = env$iteration, ev)))
}
attr(callback, 'call') <- match.call()
attr(callback, 'name') <- 'cb.evaluation.log'
callback
}
#' Callback closure for restetting the booster's parameters at each iteration.
#'
#' @param new_params a list where each element corresponds to a parameter that needs to be reset.
#' Each element's value must be either a vector of values of length \code{nrounds}
#' to be set at each iteration,
#' or a function of two parameters \code{learning_rates(iteration, nrounds)}
#' which returns a new parameter value by using the current iteration number
#' and the total number of boosting rounds.
#'
#' @details
#' This is a "pre-iteration" callback function used to reset booster's parameters
#' at the beginning of each iteration.
#'
#' Note that when training is resumed from some previous model, and a function is used to
#' reset a parameter value, the \code{nround} argument in this function would be the
#' the number of boosting rounds in the current training.
#'
#' Callback function expects the following values to be set in its calling frame:
#' \code{bst} or \code{bst_folds},
#' \code{iteration},
#' \code{begin_iteration},
#' \code{end_iteration}.
#'
#' @seealso
#' \code{\link{callbacks}}
#'
#' @export
cb.reset.parameters <- function(new_params) {
if (typeof(new_params) != "list")
stop("'new_params' must be a list")
pnames <- gsub("\\.", "_", names(new_params))
nrounds <- NULL
# run some checks in the begining
init <- function(env) {
nrounds <<- env$end_iteration - env$begin_iteration + 1
if (is.null(env$bst) && is.null(env$bst_folds))
stop("Parent frame has neither 'bst' nor 'bst_folds'")
# Some parameters are not allowed to be changed,
# since changing them would simply wreck some chaos
not_allowed <- pnames %in%
c('num_class', 'num_output_group', 'size_leaf_vector', 'updater_seq')
if (any(not_allowed))
stop('Parameters ', paste(pnames[not_allowed]), " cannot be changed during boosting.")
for (n in pnames) {
p <- new_params[[n]]
if (is.function(p)) {
if (length(formals(p)) != 2)
stop("Parameter '", n, "' is a function but not of two arguments")
} else if (is.numeric(p) || is.character(p)) {
if (length(p) != nrounds)
stop("Length of '", n, "' has to be equal to 'nrounds'")
} else {
stop("Parameter '", n, "' is not a function or a vector")
}
}
}
callback <- function(env = parent.frame()) {
if (is.null(nrounds))
init(env)
i <- env$iteration
pars <- lapply(new_params, function(p) {
if (is.function(p))
return(p(i, nrounds))
p[i]
})
if (!is.null(env$bst)) {
xgb.parameters(env$bst$handle) <- pars
} else {
for (fd in env$bst_folds)
xgb.parameters(fd$bst) <- pars
}
}
attr(callback, 'is_pre_iteration') <- TRUE
attr(callback, 'call') <- match.call()
attr(callback, 'name') <- 'cb.reset.parameters'
callback
}
#' Callback closure to activate the early stopping.
#'
#' @param stopping_rounds The number of rounds with no improvement in
#' the evaluation metric in order to stop the training.
#' @param maximize whether to maximize the evaluation metric
#' @param metric_name the name of an evaluation column to use as a criteria for early
#' stopping. If not set, the last column would be used.
#' Let's say the test data in \code{watchlist} was labelled as \code{dtest},
#' and one wants to use the AUC in test data for early stopping regardless of where
#' it is in the \code{watchlist}, then one of the following would need to be set:
#' \code{metric_name='dtest-auc'} or \code{metric_name='dtest_auc'}.
#' All dash '-' characters in metric names are considered equivalent to '_'.
#' @param verbose whether to print the early stopping information.
#'
#' @details
#' This callback function determines the condition for early stopping
#' by setting the \code{stop_condition = TRUE} flag in its calling frame.
#'
#' The following additional fields are assigned to the model's R object:
#' \itemize{
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