R: Calculate metrics.

catboost.eval_metrics {catboost}

R Documentation

Calculate metrics.

Calculate the specified metrics for the specified dataset.

catboost.eval_metrics(
  model,
  pool,
  metrics,
  ntree_start = 0L,
  ntree_end = 0L,
  eval_period = 1,
  thread_count = -1,
  tmp_dir = NULL
)

`model`	The model obtained as the result of training. Default value: Required argument
`pool`	The pool for which you want to evaluate the metrics. Default value: Required argument
`metrics`	The list of metrics to be calculated. (Supported metrics https://catboost.ai/docs/references/custom-metric__supported-metrics.html) Default value: Required argument
`ntree_start`	Model is applied on the interval [ntree_start, ntree_end) with the step eval_period (zero-based indexing). Default value: 0
`ntree_end`	Model is applied on the interval [ntree_start, ntree_end) with the step eval_period (zero-based indexing). Default value: 0 (if value equals to 0 this parameter is ignored and ntree_end equal to tree_count)
`eval_period`	Model is applied on the interval [ntree_start, ntree_end) with the step eval_period (zero-based indexing). Default value: 1
`thread_count`	The number of threads to use when applying the model. If -1, then the number of threads is set to the number of CPU cores. Allows you to optimize the speed of execution. This parameter doesn't affect results. Default value: -1
`tmp_dir`	The name of the temporary directory for intermediate results. If NULL, then the name will be generated. Default value: NULL

dict: metric -> array of shape [(ntree_end - ntree_start) / eval_period].