Concepedia

Interpretability

Interpretability is a property of predictive models in language modeling and machine learning that enables human users to understand, explain, and reason about a model's internal mechanisms and decision-making processes, distinguishing it from mere predictive accuracy by emphasizing transparency and comprehensibility.

2.5K

Publications

211.1K

Citations

9K

Authors

2.3K

Institutions

Publications per year

2017–2026

2K

Parents

Publications

2.5K

On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)

Dagstuhl Research Online Publication Server · 2024 · 13.3K citations · Full text

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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

Cynthia Rudin · Nature Machine Intelligence · 2019 · 9K citations · Full text

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A Unified Approach to Interpreting Model Predictions

Scott Lundberg, Su‐In Lee · arXiv (Cornell University) · 2017 · 7.6K citations · Full text

, , +17

The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

Takaya Saito, Marc Rehmsmeier · PLoS ONE · 2015 · 4.7K citations · Full text

, , +13

Towards A Rigorous Science of Interpretable Machine Learning

Finale Doshi‐Velez, Been Kim · arXiv (Cornell University) · 2017 · 3.2K citations · Full text

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1–5 of 2.5K

Authors

9K

  1. BK
    Been Kim

    Google (United States), United States

    19 publications · 6.2K citations

    17

    h-index

  2. FH
    Francisco Herrera

    Universidad de Granada, Spain

    12 publications · 2.9K citations

    12

    h-index

  3. JM
    José M. Alonso

    Universidade de Santiago de Compostela, Spain

    12 publications · 2K citations

    11

    h-index

  4. LM
    Luis Magdalena

    Universidad Politécnica de Madrid, Spain

    12 publications · 493 citations

    11

    h-index

  5. HI
    Hisao Ishibuchi

    Osaka Prefecture University, Japan

    11 publications · 912 citations

    10

    h-index

1–5 of 9K

Institutions

2.3K

  1. Tsinghua University

    Beijing, China

    28 h-index

    153 publications

    7.4K citations

  2. Chinese Academy of Sciences

    Beijing, China

    27 h-index

    111 publications

    7.5K citations

  3. Google (United States)

    Mountain View, United States

    24 h-index

    109 publications

    13.8K citations

  4. University of Washington

    Seattle, United States

    21 h-index

    40 publications

    45.3K citations

  5. University of Science and Technology of China

    Hefei, China

    21 h-index

    92 publications

    6.1K citations

  6. Nanyang Technological University

    Singapore, Singapore

    21 h-index

    38 publications

    5.9K citations

  7. Stanford University

    Stanford, United States

    20 h-index

    90 publications

    12.2K citations

  8. Massachusetts Institute of Technology

    Cambridge, United States

    20 h-index

    64 publications

    7K citations

1–8 of 2.3K

Venues

  1. arXiv (Cornell University)

    Repository · 288 publications · 26.5K citations

    59

    h-index

  2. IEEE Transactions on Fuzzy Systems

    TFS · 40 publications · 3.5K citations

    30

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 38 publications · 2.9K citations

    26

    h-index

  4. IEEE Access

    45 publications · 1.6K citations

    25

    h-index

  5. Scientific Reports

    26 publications · 1.5K citations

    24

    h-index

1–5