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. A rectangular data object, such as a data frame. 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. An integer vector for the number of trees in the ensemble. 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.