Time-aware Feature Selection

Time-Aware Feature Selection is a temporal feature engineering method that distinguishes itself by systematically identifying and retaining predictive features whose relevance is explicitly modeled or validated with respect to the temporal structure and dynamics of the underlying time-series data.

22

Publications

1.9K

Citations

81

Authors

48

Institutions

Publications per year

2017–2026

16

Authors

81

  1. RS
    Ramin Shokripour

    Central Washington University, United States

    1 publications · 39 citations

    1

    h-index

  2. FB
    Fatima-Zahra Belouadha

    Mohammed V University, Morocco

    1 publications · 11 citations

    1

    h-index

  3. BW
    Bo Wang

    Chinese Academy of Sciences, China

    1 publications · 34 citations

    1

    h-index

  4. BN
    Babak Nadjar Araabi

    University of Tehran, Iran

    1 publications · 67 citations

    1

    h-index

  5. FM
    Francisco Martínez‐Álvarez

    Universidad Pablo de Olavide, Spain

    1 publications · 33 citations

    1

    h-index

1–5 of 81

Venues

  1. Information Fusion

    2 publications · 463 citations

    2

    h-index

  2. Applied Soft Computing

    2 publications · 49 citations

    2

    h-index

  3. Knowledge and Information Systems

    1 publications · 390 citations

    1

    h-index

  4. ACM Transactions on Intelligent Systems and Technology

    TIST · 1 publications · 31 citations

    1

    h-index

  5. Frontiers of Computer Science

    1 publications · 84 citations

    1

    h-index

1–5