Feature Transformation

Feature Transformation is a data preprocessing technique within feature engineering that involves applying mathematical functions to existing features to improve model performance by altering their scale, distribution, or structure while preserving their semantic meaning.

734

Publications

104.7K

Citations

2.4K

Authors

797

Institutions

Publications per year

2017–2026

392

Authors

2.4K

  1. JF
    Jiashi Feng

    National University of Singapore, Singapore

    5 publications · 611 citations

    5

    h-index

  2. YW
    Yunhe Wang

    The University of Sydney, Australia

    5 publications · 4.7K citations

    5

    h-index

  3. DB
    David Benavides

    Universidad de Sevilla, Spain

    5 publications · 350 citations

    5

    h-index

  4. MZ
    Mengjie Zhang

    Victoria University of Wellington, New Zealand

    4 publications · 88 citations

    4

    h-index

  5. HL
    Haizhou Li

    National University of Singapore, Singapore

    4 publications · 83 citations

    4

    h-index

1–5 of 2.4K

Venues

  1. arXiv (Cornell University)

    Repository · 60 publications · 3.9K citations

    31

    h-index

  2. IEEE Access

    16 publications · 961 citations

    15

    h-index

  3. IEEE Transactions on Image Processing

    12 publications · 809 citations

    12

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 11 publications · 989 citations

    11

    h-index

  5. Pattern Recognition

    10 publications · 1.6K citations

    10

    h-index

1–5