Binary Splits
Binary Splits is a decision tree partitioning strategy that recursively divides a node into exactly two child nodes based on a single splitting criterion, thereby enabling hierarchical data segmentation through dichotomous logical conditions.
52
Publications
12.5K
Citations
161
Authors
84
Institutions
Publications per year
2017–2026
10
Parents
52
A working guide to boosted regression trees
Jane Elith, John R. Leathwick, Trevor Hastie · Journal of Animal Ecology · 2008 · 6.5K citations · Full text
Computing, Biostatistics, Ecology +14
SPLIT SELECTION METHODS FOR CLASSIFICATION TREES
Wei‐Yin Loh, Yu‐Shan Shih · 1997 · 943 citations
Learning relational probability trees
Jennifer Neville, David Jensen, Lisa Friedland et al. · 2003 · 215 citations
1–5 of 52
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IBM Research - Thomas J. Watson Research Center, United States
3 publications · 63 citations
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1–5 of 161
84
University of Houston
Houston, United States
3 h-index
6 publications
129 citations
Yale University
New Haven, United States
2 h-index
2 publications
139 citations

University of Alberta
Edmonton, Canada
2 h-index
6 publications
339 citations

University of Massachusetts Amherst
Amherst Center, United States
2 h-index
8 publications
936 citations

University of Toronto
Toronto, Canada
2 h-index
4 publications
154 citations
Technical University of Munich
Munich, Germany
2 h-index
2 publications
341 citations
Universitat Politècnica de Catalunya
Barcelona, Spain
2 h-index
3 publications
128 citations
National Chung Cheng University
Minxiong, Taiwan
2 h-index
2 publications
72 citations
1–8 of 84
4 publications · 135 citations
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2 publications · 139 citations
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CSDA · 2 publications · 363 citations
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2 publications · 43 citations
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2 publications · 98 citations
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