Interval-based Classification

Interval-Based Classification is a time series classification approach that represents the time series as a set of sub-intervals and extracts discriminative features from each interval to distinguish between different classes based on localized temporal patterns.

149

Publications

9.2K

Citations

365

Authors

199

Institutions

Publications per year

2017–2026

55

Authors

365

  1. JS
    José Sanz

    Universidad Pública de Navarra (UPNA), Spain

    6 publications · 584 citations

    6

    h-index

  2. HB
    Humberto Bustince

    Universidad Pública de Navarra (UPNA), Spain

    6 publications · 584 citations

    6

    h-index

  3. HI
    Hisao Ishibuchi

    Osaka Prefecture University, Japan

    6 publications · 109 citations

    6

    h-index

  4. WP
    Witold Pedrycz

    University of Alberta, Canada

    5 publications · 210 citations

    5

    h-index

  5. HT
    Hideo Tanaka

    Okayama University, Japan

    4 publications · 85 citations

    4

    h-index

1–5 of 365

Venues

  1. IEEE Transactions on Fuzzy Systems

    TFS · 6 publications · 483 citations

    6

    h-index

  2. Knowledge-Based Systems

    5 publications · 182 citations

    5

    h-index

  3. Neural Networks

    4 publications · 134 citations

    4

    h-index

  4. Data Mining and Knowledge Discovery

    3 publications · 118 citations

    4

    h-index

  5. Neurocomputing

    3 publications · 91 citations

    3

    h-index

1–5