Diversity Forests: Using Split Sampling to Enable Innovative Complex Split Procedures in Random Forests.

The diversity forest algorithm is an alternative candidate node split sampling scheme that makes innovative complex split procedures in random forests possible. While conventional univariable, binary splitting suffices for obtaining strong predictive performance, new complex split procedures can help tackling practically important issues. For example, interactions between features can be exploited effectively by bivariable splitting. With diversity forests, each split is selected from a candidate split set that is sampled in the following way: for The online version contains supplementary material available at 10.1007/s42979-021-00920-1.

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© The Author(s) 2021.

Déclaration de conflit d'intérêts

Conflict of InterestThe funding body German Science Foundation had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. The author declares that he has no conflict of interest.