# mx.callback.early.stop¶

## Description¶

Early stop with different conditions.

Early stopping applying different conditions: hard thresholds or epochs number from the best score. Tested with “epoch.end.callback” function.

## Usage¶

mx.callback.early.stop(

train.metric = NULL,

eval.metric = NULL,

maximize = FALSE,

verbose = FALSE

)


## Arguments¶

Argument

Description

train.metric

Numeric. Hard threshold for the metric of the training data set (optional)

eval.metric

Numeric. Hard threshold for the metric of the evaluating data set (if set, optional)

bad.steps

Integer. How much epochs should gone from the best score? Use this option with evaluation data set

maximize

Logical. Do your model use maximizing or minimizing optimization?

verbose

Logical