Cargando…
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 hel...
Autor principal: | Hornung, Roman |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8533673/ https://www.ncbi.nlm.nih.gov/pubmed/34723205 http://dx.doi.org/10.1007/s42979-021-00920-1 |
Ejemplares similares
-
Splitting on categorical predictors in random forests
por: Wright, Marvin N., et al.
Publicado: (2019) -
Block Forests: random forests for blocks of clinical and omics covariate data
por: Hornung, Roman, et al.
Publicado: (2019) -
On the overestimation of random forest’s out-of-bag error
por: Janitza, Silke, et al.
Publicado: (2018) -
Splitting random forest (SRF) for determining compact sets of genes that distinguish between cancer subtypes
por: Guan, Xiaowei, et al.
Publicado: (2012) -
Split obturator: An innovative approach
por: Jurel, Sunit K., et al.
Publicado: (2011)