Study of Hellinger Distance as a splitting metric for Random Forests in balanced and imbalanced classification datasets-Reference-Cited by-同舟云学术

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Study of Hellinger Distance as a splitting metric for Random Forests in balanced and imbalanced classification datasets

Published:2020-07 Issue: Volume:149 Page:113264
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Aler Ricardo^ORCID,Valls José M.^ORCID,Boström Henrik

Funder

Spanish Ministry of Science

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference33 articles.

1. Mlr: Machine learning in r;Bischl;Journal of Machine Learning Research,2016

2. Image classification using random forests and ferns;Bosch,2007

3. Bagging predictors;Breiman;Machine Learning,1996

4. Random forests;Breiman;Machine Learning,2001

5. Classification and regression trees;Breiman,2017

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