Polynomial Features

Polynomial Features is a feature engineering technique that generates new predictive variables by computing all possible combinations of original features raised to a specified degree, thereby capturing nonlinear relationships through polynomial expansion within a supervised learning framework.

45

Publications

10.5K

Citations

155

Authors

83

Institutions

Publications per year

2017–2026

15

Authors

155

  1. ZY
    Zejian Yuan

    Xi'an Jiaotong University, China

    2 publications · 226 citations

    2

    h-index

  2. AS
    Alessandro S. Martins

    Universidade Estadual Paulista (Unesp), Brazil

    2 publications · 106 citations

    2

    h-index

  3. JC
    Juan Carlos Gómez

    National University of Rosario, Argentina

    2 publications · 68 citations

    2

    h-index

  4. EL
    Edna Lúcia Flôres

    Universidade Federal de Uberlândia, Brazil

    2 publications · 106 citations

    2

    h-index

  5. KA
    Khaled Assaleh

    American University of Sharjah, United Arab Emirates

    2 publications · 54 citations

    2

    h-index

1–5 of 155

Venues

  1. Expert Systems with Applications

    3 publications · 182 citations

    3

    h-index

  2. 2

    h-index

  3. Pattern Recognition

    2 publications · 100 citations

    2

    h-index

  4. Biomedical Signal Processing and Control

    1 publications · 12 citations

    1

    h-index

  5. 1

    h-index

1–5