Label Error Prevention

Label Error Prevention is a methodological framework within the domain of data quality management that specifically identifies, mitigates, and prevents inaccuracies in labeled datasets through systematic validation, correction, and monitoring processes to ensure the reliability of supervised learning models.

10

Publications

407

Citations

51

Authors

20

Institutions

Publications per year

2017–2026

10

Authors

51

  1. SY
    Shuang Yao

    China Jiliang University, China

    1 publications · 98 citations

    1

    h-index

  2. MZ
    Mattia Zeni

    University of Trento, Italy

    1 publications · 41 citations

    1

    h-index

  3. MW
    Min Wang

    National University of Defense Technology, China

    1 publications · 25 citations

    1

    h-index

  4. KF
    Ke Fu

    Southwest Petroleum University, China

    1 publications · 25 citations

    1

    h-index

  5. CW
    Chaoyang Wang

    Xi'an Jiaotong University, China

    1 publications · 96 citations

    1

    h-index

1–5 of 51

Venues