The dataset being composed of 14 groups, cross-validation procedures by removing 1 group, 2 groups or 7 groups are evaluated to estimate generalisation performances. Fig. 2.1k. presents the results with 1 group out. The classification of IN is hard for 3 groups, the 3 test sets of the leave-1-group-out procedure. A comparison of the confusion matrices obtained with these procedures is given in Tab. 2.1b. by averaging the proportion of samples by groups and classes, By retaining in each group the main feature, noted *, with the highest value of AUC, the set of features can be reduced to: FALL LOG ,
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