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[R] put 'verbose' in correct argument (#9942)

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david-cortes 2024-01-02 08:20:51 +01:00 committed by GitHub
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commit 32cbab1cc0
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2 changed files with 16 additions and 16 deletions
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16
R-package/R/xgb.train.R
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@ -251,9 +251,9 @@
#' watchlist <- list(train = dtrain, eval = dtest) #' watchlist <- list(train = dtrain, eval = dtest)
#' #'
#' ## A simple xgb.train example: #' ## A simple xgb.train example:
#' param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread, #' param <- list(max_depth = 2, eta = 1, nthread = nthread,
#' objective = "binary:logistic", eval_metric = "auc") #' objective = "binary:logistic", eval_metric = "auc")
#' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist) #' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0)
#' #'
#' ## An xgb.train example where custom objective and evaluation metric are #' ## An xgb.train example where custom objective and evaluation metric are
#' ## used: #' ## used:
@ -272,13 +272,13 @@
#' #'
#' # These functions could be used by passing them either: #' # These functions could be used by passing them either:
#' # as 'objective' and 'eval_metric' parameters in the params list: #' # as 'objective' and 'eval_metric' parameters in the params list:
#' param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread, #' param <- list(max_depth = 2, eta = 1, nthread = nthread,
#' objective = logregobj, eval_metric = evalerror) #' objective = logregobj, eval_metric = evalerror)
#' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist) #' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0)
#' #'
#' # or through the ... arguments: #' # or through the ... arguments:
#' param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread) #' param <- list(max_depth = 2, eta = 1, nthread = nthread)
#' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, #' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0,
#' objective = logregobj, eval_metric = evalerror) #' objective = logregobj, eval_metric = evalerror)
#' #'
#' # or as dedicated 'obj' and 'feval' parameters of xgb.train: #' # or as dedicated 'obj' and 'feval' parameters of xgb.train:
@ -287,10 +287,10 @@
#' #'
#' #'
#' ## An xgb.train example of using variable learning rates at each iteration: #' ## An xgb.train example of using variable learning rates at each iteration:
#' param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread, #' param <- list(max_depth = 2, eta = 1, nthread = nthread,
#' objective = "binary:logistic", eval_metric = "auc") #' objective = "binary:logistic", eval_metric = "auc")
#' my_etas <- list(eta = c(0.5, 0.1)) #' my_etas <- list(eta = c(0.5, 0.1))
#' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, #' bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0,
#' callbacks = list(cb.reset.parameters(my_etas))) #' callbacks = list(cb.reset.parameters(my_etas)))
#' #'
#' ## Early stopping: #' ## Early stopping:

16
R-package/man/xgb.train.Rd
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@ -303,9 +303,9 @@ dtest <- with(
watchlist <- list(train = dtrain, eval = dtest) watchlist <- list(train = dtrain, eval = dtest)
## A simple xgb.train example: ## A simple xgb.train example:
param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread, param <- list(max_depth = 2, eta = 1, nthread = nthread,
objective = "binary:logistic", eval_metric = "auc") objective = "binary:logistic", eval_metric = "auc")
bst <- xgb.train(param, dtrain, nrounds = 2, watchlist) bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0)
## An xgb.train example where custom objective and evaluation metric are ## An xgb.train example where custom objective and evaluation metric are
## used: ## used:
@ -324,13 +324,13 @@ evalerror <- function(preds, dtrain) {
# These functions could be used by passing them either: # These functions could be used by passing them either:
# as 'objective' and 'eval_metric' parameters in the params list: # as 'objective' and 'eval_metric' parameters in the params list:
param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread, param <- list(max_depth = 2, eta = 1, nthread = nthread,
objective = logregobj, eval_metric = evalerror) objective = logregobj, eval_metric = evalerror)
bst <- xgb.train(param, dtrain, nrounds = 2, watchlist) bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0)
# or through the ... arguments: # or through the ... arguments:
param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread) param <- list(max_depth = 2, eta = 1, nthread = nthread)
bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0,
objective = logregobj, eval_metric = evalerror) objective = logregobj, eval_metric = evalerror)
# or as dedicated 'obj' and 'feval' parameters of xgb.train: # or as dedicated 'obj' and 'feval' parameters of xgb.train:
@ -339,10 +339,10 @@ bst <- xgb.train(param, dtrain, nrounds = 2, watchlist,
## An xgb.train example of using variable learning rates at each iteration: ## An xgb.train example of using variable learning rates at each iteration:
param <- list(max_depth = 2, eta = 1, verbose = 0, nthread = nthread, param <- list(max_depth = 2, eta = 1, nthread = nthread,
objective = "binary:logistic", eval_metric = "auc") objective = "binary:logistic", eval_metric = "auc")
my_etas <- list(eta = c(0.5, 0.1)) my_etas <- list(eta = c(0.5, 0.1))
bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, bst <- xgb.train(param, dtrain, nrounds = 2, watchlist, verbose = 0,
callbacks = list(cb.reset.parameters(my_etas))) callbacks = list(cb.reset.parameters(my_etas)))
## Early stopping: ## Early stopping: