Decision Tree Classification

Decision Tree Classification is a supervised machine learning algorithm that belongs to the family of tree-based models, distinguished by its use of a hierarchical, rule-based structure to recursively partition feature space into discrete class labels based on optimal split criteria derived from training data.

3.5K

Publications

241.1K

Citations

11.4K

Authors

3.4K

Institutions

Publications per year

2017–2026

1.6K

Authors

11.4K

  1. AC
    André C. P. L. F. de Carvalho

    Universidade de São Paulo, Brazil

    11 publications · 793 citations

    11

    h-index

  2. AA
    Alex A. Freitas

    University of Kent, United Kingdom

    11 publications · 1.9K citations

    11

    h-index

  3. JA
    Joaquín Abellán

    Universidad de Granada, Spain

    9 publications · 725 citations

    9

    h-index

  4. DM
    Dewan Md. Farid

    United International University, Bangladesh

    9 publications · 528 citations

    9

    h-index

  5. PK
    Peter Kokol

    University of Maribor, Slovenia

    9 publications · 295 citations

    9

    h-index

1–5 of 11.4K

Venues

  1. Expert Systems with Applications

    48 publications · 5K citations

    36

    h-index

  2. IEEE Access

    36 publications · 2.4K citations

    24

    h-index

  3. International Journal of Computer Applications

    51 publications · 2.7K citations

    23

    h-index

  4. Remote Sensing

    29 publications · 1.8K citations

    23

    h-index

  5. Procedia Computer Science

    36 publications · 2.8K citations

    23

    h-index

1–5