Scalable Classification

Scalable Classification is a machine learning methodology designed to efficiently handle growing datasets and feature dimensions while maintaining classification accuracy and computational tractability.

211

Publications

13.3K

Citations

573

Authors

274

Institutions

Publications per year

2017–2026

76

Authors

573

  1. FH
    Francisco Herrera

    Universidad de Granada, Spain

    6 publications · 149 citations

    6

    h-index

  2. FM
    Francesco Marcelloni

    University of Pisa, Italy

    4 publications · 231 citations

    4

    h-index

  3. AF
    Alberto Fernández

    Universidad de Granada, Spain

    4 publications · 77 citations

    4

    h-index

  4. CB
    Christos-Savvas Bouganis

    Imperial College London, United Kingdom

    4 publications · 189 citations

    4

    h-index

  5. FB
    Florin Baboescu

    University of California San Diego, United States

    3 publications · 525 citations

    3

    h-index

1–5 of 573

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 1.6K citations

    9

    h-index

  2. IEEE/ACM Transactions on Networking

    TON · 5 publications · 336 citations

    5

    h-index

  3. Expert Systems with Applications

    5 publications · 181 citations

    5

    h-index

  4. Procedia Computer Science

    5 publications · 108 citations

    5

    h-index

  5. Journal Of Big Data

    4 publications · 329 citations

    4

    h-index

1–5