For some models, predictions can be made on sub-models in the model object.

# S3 method for `_catboost.Model`
multi_predict(
  object,
  new_data,
  type = NULL,
  trees = NULL,
  categorical_cols = NULL,
  ...
)

Arguments

object

A model_fit object.

new_data

A rectangular data object, such as a data frame.

type

A single character value or NULL. Possible values are "numeric", "class", "prob", "conf_int", "pred_int", "quantile", or "raw". When NULL, predict() will choose an appropriate value based on the model's mode.

trees

An integer vector for the number of trees in the ensemble.

categorical_cols

indices of categorical columns, when NULL (default) factor columns are automatically detected.

...

Optional arguments to pass to predict.model_fit(type = "raw") such as type.