R: Sum models.

catboost.sum_models {catboost} | R Documentation

## Sum models.

### Description

Blend trees and counters of two or more trained CatBoost models into a new model. Leaf values can be individually weighted for each input model. For example, it may be useful to blend models trained on different validation datasets.

### Usage

    catboost.sum_models(
      models,
      weights = NULL,
      ctr_merge_policy = "IntersectingCountersAverage"
    )

### Arguments

`models` | Models for the summation. Default value: Required argument
`weights` | The weights of the models. Default value: NULL (use weight 1 for every model)
`ctr_merge_policy` | The counters merging policy. Possible values: 'FailIfCtrIntersects' Ensure that the models have zero intersecting counters 'LeaveMostDiversifiedTable' Use the most diversified counters by the count of unique hash values 'IntersectingCountersAverage' Use the average ctr counter values in the intersecting bins Default value: 'IntersectingCountersAverage'

### Value

Model object.

[Package catboost version 0.26.1 Index]