Log Loss

Log Loss is a probabilistic loss function used in classification tasks that measures the performance of a model by penalizing incorrect predictions based on their deviation from the true class labels, where the penalty increases logarithmically as the predicted probability diverges from the actual outcome.

118

Publications

6.7K

Citations

357

Authors

170

Institutions

Publications per year

2017–2026

62

Authors

357

  1. PG
    Peter Grünwald

    Centrum Wiskunde & Informatica, Netherlands

    5 publications · 144 citations

    5

    h-index

  2. JW
    Janet W. Hartley

    National Institute of Allergy and Infectious Diseases, United States

    4 publications · 221 citations

    4

    h-index

  3. WP
    Wallace P. Rowe

    National Institute of Allergy and Infectious Diseases, United States

    4 publications · 221 citations

    4

    h-index

  4. NA
    Nishant A. Mehta

    Georgia Institute of Technology, United States

    3 publications · 105 citations

    3

    h-index

  5. MK
    Manfred K. Warmuth

    University of California, Santa Cruz, United States

    3 publications · 349 citations

    3

    h-index

1–5 of 357

Venues

  1. arXiv (Cornell University)

    Repository · 18 publications · 679 citations

    17

    h-index

  2. The Journal of Experimental Medicine

    4 publications · 221 citations

    4

    h-index

  3. IEEE Access

    3 publications · 351 citations

    3

    h-index

  4. Journal of Quantitative Analysis in Sports

    2 publications · 64 citations

    2

    h-index

  5. 2

    h-index

1–5