Web: http://arxiv.org/abs/2209.07623

Sept. 19, 2022, 1:11 a.m. | Benjamin Ledel, Steffen Herbold

cs.LG updates on arXiv.org arxiv.org

Context: The identification of bugs within the reported issues in an issue
tracker is crucial for the triage of issues. Machine learning models have shown
promising results regarding the performance of automated issue type prediction.
However, we have only limited knowledge beyond our assumptions how such models
identify bugs. LIME and SHAP are popular technique to explain the predictions
of classifiers.

Objective: We want to understand if machine learning models provide
explanations for the classification that are reasonable to us …

arxiv lime prediction shap studying

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