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

Authors

161

  1. YS
    Yu‐Shan Shih

    National Chung Cheng University, Taiwan

    3 publications · 1K citations

    3

    h-index

  2. CK
    C. K. Wong

    IBM Research - Thomas J. Watson Research Center, United States

    3 publications · 63 citations

    3

    h-index

  3. SS
    Shou‐Hsuan Stephen Huang

    University of Houston, United States

    3 publications · 63 citations

    3

    h-index

  4. DS
    D. S. Hirschberg

    University of California, Irvine, United States

    2 publications · 45 citations

    2

    h-index

  5. HZ
    Heping Zhang

    Yale University, United States

    2 publications · 139 citations

    2

    h-index

1–5 of 161

Venues

  1. Pattern Recognition

    4 publications · 135 citations

    4

    h-index

  2. 2

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 2 publications · 363 citations

    2

    h-index

  4. Journal of Algorithms

    2 publications · 43 citations

    2

    h-index

  5. Acta Informatica

    2 publications · 98 citations

    2

    h-index

1–5