Temporal Missingness Features

Temporal Missingness Features is a temporal feature engineering construct that encodes patterns of missing data over time by capturing the temporal structure and duration of gaps in time series observations, distinguishing it from general imputation or static missingness indicators through its explicit modeling of time-based absence dynamics.

6

Publications

445

Citations

20

Authors

16

Institutions

Publications per year

2017–2026

2

Authors

20

  1. HS
    Huanfeng Shen

    Wuhan University, China

    1 publications · 320 citations

    1

    h-index

  2. WH
    William Harrett

    Cairo University, Egypt

    1 publications · 13 citations

    1

    h-index

  3. NR
    Naren Ramakrishnan

    Virginia Tech, United States

    1 publications · 19 citations

    1

    h-index

  4. CL
    Chang‐Tien Lu

    Virginia Tech, United States

    1 publications · 19 citations

    1

    h-index

  5. CL
    Chao Li

    Zhejiang University, China

    1 publications · 18 citations

    1

    h-index

1–5 of 20

Venues

  1. Remote Sensing of Environment

    1 publications · 320 citations

    1

    h-index

  2. Canadian Journal of Civil Engineering

    1 publications · 13 citations

    1

    h-index

  3. Ecological Modelling

    1 publications · 41 citations

    1

    h-index

  4. IEEE Transactions on Big Data

    1 publications · 10 citations

  5. Big Data Mining and Analytics

    1 publications · 13 citations

1–5