GRASP uses Shapley values and group L21 regularization to identify fewer, less redundant, and more stable features for medical predictions while matching or exceeding the accuracy of prior methods.
These data offer great potential for precision medicine, but their high dimensionality and noise pose major challenges for knowledge discovery [1]
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GRASP: group-Shapley feature selection for patients
GRASP uses Shapley values and group L21 regularization to identify fewer, less redundant, and more stable features for medical predictions while matching or exceeding the accuracy of prior methods.