Data Leakage

Data Leakage is a phenomenon in machine learning wherein information from outside the training dataset or future time periods inadvertently influences the model during training, leading to overly optimistic performance estimates and invalid generalization assessment.

622

Publications

38.4K

Citations

2.3K

Authors

840

Institutions

Publications per year

2017–2026

461

Authors

2.3K

  1. AK
    Ashutosh Kumar Singh

    National Institute of Technology Kurukshetra, India

    13 publications · 411 citations

    13

    h-index

  2. IG
    Ishu Gupta

    National Institute of Technology Kurukshetra, India

    13 publications · 402 citations

    13

    h-index

  3. CS
    Congzheng Song

    Cornell University, United States

    7 publications · 5.1K citations

    7

    h-index

  4. YE
    Yuval Elovici

    Ben-Gurion University of the Negev, Israel

    6 publications · 223 citations

    6

    h-index

  5. MG
    Mohsen Guizani

    Qatar University, Qatar

    5 publications · 142 citations

    5

    h-index

1–5 of 2.3K

Venues

  1. arXiv (Cornell University)

    Repository · 48 publications · 1.8K citations

    22

    h-index

  2. IEEE Access

    19 publications · 1.1K citations

    16

    h-index

  3. IEEE Internet of Things Journal

    12 publications · 1.4K citations

    12

    h-index

  4. IEEE Transactions on Industrial Informatics

    12 publications · 1.9K citations

    12

    h-index

  5. IEEE Network

    5 publications · 637 citations

    5

    h-index

1–5