diversityForest-package {diversityForest}R Documentation

Diversity Forests

Description

The diversity forest algorithm is a split-finding approach that enables complex split procedures to be realized in random forest variants. This is achieved by drastically reducing the number of candidate splits evaluated at each node. It also avoids the variable selection bias seen in conventional random forests, where 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 methodologies which use the diversity forest algorithm:

Diversity forests with univariable, binary splitting can be constructed using the function divfor, interaction forests using the function interactionfor, and the class-focused and the discriminatory VIM can be computed using the function multifor. The former two methods 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 0.6.0 Index]