Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Deprecate reg:linear' in favor of reg:squarederror'. (#4267)

Browse Source 
* Deprecate `reg:linear' in favor of `reg:squarederror'.
* Replace the use of `reg:linear'.
* Replace the use of `silent`.
This commit is contained in:
Jiaming Yuan
2019-03-17 17:55:04 +08:00
committed by GitHub
parent cf8d5b9b76
commit 29a1356669
34 changed files with 210 additions and 193 deletions
Download Patch File Download Diff File Expand all files Collapse all files

67
R-package/R/utils.R
View File

@@ -28,12 +28,12 @@ NVL <- function(x, val) {
# Merges booster params with whatever is provided in ...
# plus runs some checks
check.booster.params <- function(params, ...) {
if (typeof(params) != "list")
if (typeof(params) != "list")
stop("params must be a list")
# in R interface, allow for '.' instead of '_' in parameter names
names(params) <- gsub("\\.", "_", names(params))
# merge parameters from the params and the dots-expansion
dot_params <- list(...)
names(dot_params) <- gsub("\\.", "_", names(dot_params))
@@ -41,15 +41,15 @@ check.booster.params <- function(params, ...) {
names(dot_params))) > 0)
stop("Same parameters in 'params' and in the call are not allowed. Please check your 'params' list.")
params <- c(params, dot_params)
# providing a parameter multiple times makes sense only for 'eval_metric'
name_freqs <- table(names(params))
multi_names <- setdiff(names(name_freqs[name_freqs > 1]), 'eval_metric')
if (length(multi_names) > 0) {
warning("The following parameters were provided multiple times:\n\t",
paste(multi_names, collapse = ', '), "\n Only the last value for each of them will be used.\n")
# While xgboost internals would choose the last value for a multiple-times parameter,
# enforce it here in R as well (b/c multi-parameters might be used further in R code,
# While xgboost internals would choose the last value for a multiple-times parameter,
# enforce it here in R as well (b/c multi-parameters might be used further in R code,
# and R takes the 1st value when multiple elements with the same name are present in a list).
for (n in multi_names) {
del_idx <- which(n == names(params))
@@ -57,25 +57,25 @@ check.booster.params <- function(params, ...) {
params[[del_idx]] <- NULL
}
}
# for multiclass, expect num_class to be set
if (typeof(params[['objective']]) == "character" &&
substr(NVL(params[['objective']], 'x'), 1, 6) == 'multi:' &&
as.numeric(NVL(params[['num_class']], 0)) < 2) {
stop("'num_class' > 1 parameter must be set for multiclass classification")
}
# monotone_constraints parser
if (!is.null(params[['monotone_constraints']]) &&
typeof(params[['monotone_constraints']]) != "character") {
vec2str = paste(params[['monotone_constraints']], collapse = ',')
vec2str = paste0('(', vec2str, ')')
params[['monotone_constraints']] = vec2str
}
# interaction constraints parser (convert from list of column indices to string)
if (!is.null(params[['interaction_constraints']]) &&
if (!is.null(params[['interaction_constraints']]) &&
typeof(params[['interaction_constraints']]) != "character"){
# check input class
if (class(params[['interaction_constraints']]) != 'list') stop('interaction_constraints should be class list')
@@ -96,10 +96,10 @@ check.booster.params <- function(params, ...) {
check.custom.obj <- function(env = parent.frame()) {
if (!is.null(env$params[['objective']]) && !is.null(env$obj))
stop("Setting objectives in 'params' and 'obj' at the same time is not allowed")
if (!is.null(env$obj) && typeof(env$obj) != 'closure')
stop("'obj' must be a function")
# handle the case when custom objective function was provided through params
if (!is.null(env$params[['objective']]) &&
typeof(env$params$objective) == 'closure') {
@@ -113,21 +113,21 @@ check.custom.obj <- function(env = parent.frame()) {
check.custom.eval <- function(env = parent.frame()) {
if (!is.null(env$params[['eval_metric']]) && !is.null(env$feval))
stop("Setting evaluation metrics in 'params' and 'feval' at the same time is not allowed")
if (!is.null(env$feval) && typeof(env$feval) != 'closure')
stop("'feval' must be a function")
# handle a situation when custom eval function was provided through params
if (!is.null(env$params[['eval_metric']]) &&
typeof(env$params$eval_metric) == 'closure') {
env$feval <- env$params$eval_metric
env$params$eval_metric <- NULL
}
# require maximize to be set when custom feval and early stopping are used together
if (!is.null(env$feval) &&
is.null(env$maximize) && (
!is.null(env$early_stopping_rounds) ||
!is.null(env$early_stopping_rounds) ||
has.callbacks(env$callbacks, 'cb.early.stop')))
stop("Please set 'maximize' to indicate whether the evaluation metric needs to be maximized or not")
}
@@ -154,15 +154,15 @@ xgb.iter.update <- function(booster_handle, dtrain, iter, obj = NULL) {
# Evaluate one iteration.
# Returns a named vector of evaluation metrics
# Returns a named vector of evaluation metrics
# with the names in a 'datasetname-metricname' format.
xgb.iter.eval <- function(booster_handle, watchlist, iter, feval = NULL) {
if (!identical(class(booster_handle), "xgb.Booster.handle"))
stop("class of booster_handle must be xgb.Booster.handle")
if (length(watchlist) == 0)
if (length(watchlist) == 0)
return(NULL)
evnames <- names(watchlist)
if (is.null(feval)) {
msg <- .Call(XGBoosterEvalOneIter_R, booster_handle, as.integer(iter), watchlist, as.list(evnames))
@@ -189,7 +189,7 @@ xgb.iter.eval <- function(booster_handle, watchlist, iter, feval = NULL) {
# Generates random (stratified if needed) CV folds
generate.cv.folds <- function(nfold, nrows, stratified, label, params) {
# cannot do it for rank
if (exists('objective', where = params) &&
is.character(params$objective) &&
@@ -209,13 +209,14 @@ generate.cv.folds <- function(nfold, nrows, stratified, label, params) {
if (exists('objective', where = params) &&
is.character(params$objective)) {
# If 'objective' provided in params, assume that y is a classification label
# unless objective is reg:linear
if (params$objective != 'reg:linear')
# unless objective is reg:squarederror
if (params$objective != 'reg:squarederror')
y <- factor(y)
} else {
# If no 'objective' given in params, it means that user either wants to use
# the default 'reg:linear' objective or has provided a custom obj function.
# Here, assume classification setting when y has 5 or less unique values:
# If no 'objective' given in params, it means that user either wants to
# use the default 'reg:squarederror' objective or has provided a custom
# obj function. Here, assume classification setting when y has 5 or less
# unique values:
if (length(unique(y)) <= 5)
y <- factor(y)
}
@@ -293,22 +294,22 @@ xgb.createFolds <- function(y, k = 10)
#
#' Deprecation notices.
#'
#'
#' At this time, some of the parameter names were changed in order to make the code style more uniform.
#' The deprecated parameters would be removed in the next release.
#'
#'
#' To see all the current deprecated and new parameters, check the \code{xgboost:::depr_par_lut} table.
#'
#' A deprecation warning is shown when any of the deprecated parameters is used in a call.
#' An additional warning is shown when there was a partial match to a deprecated parameter
#'
#' A deprecation warning is shown when any of the deprecated parameters is used in a call.
#' An additional warning is shown when there was a partial match to a deprecated parameter
#' (as R is able to partially match parameter names).
#'
#'
#' @name xgboost-deprecated
NULL
# Lookup table for the deprecated parameters bookkeeping
depr_par_lut <- matrix(c(
'print.every.n', 'print_every_n',
'print.every.n', 'print_every_n',
'early.stop.round', 'early_stopping_rounds',
'training.data', 'data',
'with.stats', 'with_stats',