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docs: xgboost
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be-marc committed Aug 18, 2024
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3 changes: 2 additions & 1 deletion R/LearnerClassifXgboost.R
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#'
#' @section Early Stopping and Validation:
#' In order to monitor the validation performance during the training, you can set the `$validate` field of the Learner.
#' For information on how to configure the valdiation set, see the *Validation* section of [`mlr3::Learner`].
#' For information on how to configure the valdiation set, see the *Validation* section of [mlr3::Learner].
#' This validation data can also be used for early stopping, which can be enabled by setting the `early_stopping_rounds` parameter.
#' The final (or in the case of early stopping best) validation scores can be accessed via `$internal_valid_scores`, and the optimal `nrounds` via `$internal_tuned_values`.
#' The internal validation measure can be set via the `eval_metric` parameter that can be a [mlr3::Measure], a function, or a character string for the internal xgboost measures.
#' Using an [mlr3::Measure] is slower than the internal xgboost measures, but allows to use the same measure for tuning and validation.
#'
#' @templateVar id classif.xgboost
#' @template learner
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10 changes: 5 additions & 5 deletions man/mlr_learners_classif.xgboost.Rd

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