Validity of Feature Importance in Low-Performing Machine Learning for
Tabular Biomedical Data
Validity of Feature Importance in Low-Performing Machine Learning for
Tabular Biomedical Data
In tabular biomedical data analysis, tuning models to high accuracy is considered a prerequisite for discussing feature importance, as medical practitioners expect the validity of feature importance to correlate with performance. In this work, we challenge the prevailing belief, showing that low-performing models may also be used for feature importance. …