Symbolic Classification

Symbolic Classification is a machine learning task within symbolic systems that involves assigning input data to predefined categories based on symbolic representations and syntactic or semantic patterns derived through symbolic reasoning or genetic programming.

124

Publications

6.8K

Citations

316

Authors

144

Institutions

Publications per year

2017–2026

23

Authors

316

  1. GG
    Geoffrey G. Towell

    University of Wisconsin–Madison, United States

    3 publications · 592 citations

    3

    h-index

  2. JS
    Jude Shavlik

    University of Wisconsin–Madison, United States

    3 publications · 592 citations

    3

    h-index

  3. RJ
    Raymond J. Mooney

    The University of Texas at Austin, United States

    3 publications · 592 citations

    3

    h-index

  4. AD
    Adnan Darwiche

    University of California, Los Angeles, United States

    2 publications · 64 citations

    2

    h-index

  5. FE
    Floriana Esposito

    University of Bari Aldo Moro, Italy

    2 publications · 65 citations

    2

    h-index

1–5 of 316

Venues

  1. Machine Learning

    5 publications · 1.5K citations

    5

    h-index

  2. Pattern Recognition Letters

    4 publications · 121 citations

    4

    h-index

  3. Fuzzy Sets and Systems

    3 publications · 81 citations

    3

    h-index

  4. Africa

    3 publications · 76 citations

    3

    h-index

  5. Knowledge-Based Systems

    2 publications · 51 citations

    2

    h-index

1–5