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Table 8 Mean RF accuracies and F1-scores (in %) for the AIBL data set (no information rate 57.14%)

From: Data analysis with Shapley values for automatic subject selection in Alzheimer’s disease data sets using interpretable machine learning

Exclusion method Zero-cutoff Max valid Max test
  n ACC (in %) F1 (in %) n ACC (in %) F1 (in %) n ACC (in %) F1 (in %)
Random (-) 41 58.57 66.42 445 66.07 75.81
LOO (LR) 84 62.50 68.81 102 56.79 64.44 402 68.21 76.33
LOO (RF) 49 57.86 65.40 23 61.79 69.45 186 68.93 76.63
Data Shapley (LR) 152 61.79 69.52 340 61.07 65.79 399 73.57 75.74
Data Shapley (RF) 164 57.86 68.94 134 60.36 70.05 14 65.36 72.30
  1. Different methods were used to identify and focus on the training subjects with the most informative data. The zero-cutoff method excluded all training subjects with Data Shapley values smaller than zero. Max valid was the threshold achieved by maximizing the results for the independent validation set. Max test was the optimistic threshold which achieved the best results for the test set. Ten repetitions with different seeds were performed for every exclusion data set. The best results are highlighted in bold