R: Callback closure to activate the early stopping.

cb.early.stop {xgboost} | R Documentation

## Callback closure to activate the early stopping.

### Description

Callback closure to activate the early stopping.

### Usage

    cb.early.stop(
      stopping_rounds,
      maximize = FALSE,
      metric_name = NULL,
      verbose = TRUE
    )

### Arguments

`stopping_rounds` | The number of rounds with no improvement in the evaluation metric in order to stop the training.
`maximize` | whether to maximize the evaluation metric
`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 `watchlist` was labelled as `dtest`, and one wants to use the AUC in test data for early stopping regardless of where it is in the `watchlist`, then one of the following would need to be set: `metric_name='dtest-auc'` or `metric_name='dtest_auc'`. All dash '-' characters in metric names are considered equivalent to '_'.
`verbose` | whether to print the early stopping information.

### Details

This callback function determines the condition for early stopping by setting the `stop_condition = TRUE` flag in its calling frame.

The following additional fields are assigned to the model's R object:

- `best_score` the evaluation score at the best iteration

- `best_iteration` at which boosting iteration the best score has occurred (1-based index)

- `best_ntreelimit` to use with the `ntreelimit` parameter in `predict`. It differs from `best_iteration` in multiclass or random forest settings.

The Same values are also stored as xgb-attributes:

- `best_iteration` is stored as a 0-based iteration index (for interoperability of binary models)

- `best_msg` message string is also stored.

At least one data element is required in the evaluation watchlist for early stopping to work.

Callback function expects the following values to be set in its calling frame: `stop_condition`, `bst_evaluation`, `rank`, `bst` (or `bst_folds` and `basket`), `iteration`, `begin_iteration`, `end_iteration`, `num_parallel_tree`.

### See Also

`callbacks`, `xgb.attr`

[Package xgboost version 1.3.0.1 Index]