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Table 3 Average AUC scores of RF, XGB, and LR models trained on CNA data, estimated using 10 runs of 5-fold cross validation

From: Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data

# Features RF XGB LR
10 0.57 0.56 0.58
20 0.61 0.61 0.61
30 0.61 0.61 0.61
40 0.63 0.62 0.61
50 0.64 0.64 0.62
60 0.65 0.65 0.63
70 0.65 0.65 0.63
80 0.65 0.65 0.62
90 0.66 0.66 0.63
100 0.66 0.66 0.62
Max 0.66 0.66 0.63
Avg. 0.63 0.63 0.62