diversityForest-package {diversityForest}R Documentation

Diversity Forests

Description

The diversity forest algorithm is a split-finding approach that allows complex split procedures to be realized in random forest variants. This is achieved by drastically reducing the numbers of candidate splits that need to be evaluated for each split. The algorithm also avoids the well-known variable selection bias in conventional random forests that has the effect that variables with many possible splits are selected too frequently for splitting (Strobl et al., 2007). For details, see Hornung (2022).

Details

This package currently features three types of diversity forests:

Diversity forests with univariable, binary splitting can be constructed using the function divfor, interaction forests using the function interactionfor, and multi forests using the function multifor. Except for multi forests, which are tailored for multi-class outcomes, all included diversity forest variants support categorical, metric, and survival outcomes.

This package is a fork of the R package 'ranger' that implements random forests using an efficient C++ implementation. The documentation is in large parts taken from 'ranger', where some parts of the documentation may not apply to (the current version of) the 'diversityForest' package.

Details on further functionalities of the code that are not presented in the help pages of 'diversityForest' are found in the help pages of 'ranger', version 0.11.0, because 'diversityForest' is based on the latter version of 'ranger'. The code in the example sections can be used as a template for all basic application scenarios with respect to classification, regression and survival prediction.

References


[Package diversityForest version 0.5.0 Index]