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Table 6 F1-Scores obtained for the best standard filtering approach and best ML classifier across the different simulations. The consensus call of at least four out of the 7 tools was the winner option for the first category while GBDT model for the second

From: NeoMutate: an ensemble machine learning framework for the prediction of somatic mutations in cancer

Method Category Description S1 S2 S3 S4
GBDT ML Gradient boosting decision tree 0.9742 0.9762 0.9658 0.8748
cons_4 Standard filtering Consensus of > = 4 tools 0.9139 0.9326 0.9203 0.8044