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Table 5 Machine learning experiment test results on the gene sets with the binary representation model

From: Statistical representation models for mutation information within genomic data

Gene Set Algorithm Data Rep. Accuracy F-Score Precision Recall Roc-Auc FPR
causal LR binary 36.81 ± 0.45 36.36 ± 0.50 35.93 ± 0.52 36.81 ± 0.45 0.63 ± 0.03 9.03 ± 0.10
causal SVM-linear binary 33.53 ± 0.32 32.70 ± 0.99 31.92 ± 1.13 33.53 ± 0.32 0.62 ± 0.05 9.38 ± 011
causal Perceptron binary 36.74 ± 0.56 36.62 ± 0.83 36.52 ± 2.56 36.74 ± 0.56 0.63 ± 0.06 10.01 ± 0.10
all LR binary 67.19 ± 0.41 68.01 ± 0.01 68.01 ± 0.00 67.01 ± 0.01 0.78 ± 0.01 3.85 ± 0.07
all SVM-linear binary 68.46 ± 0.67 68.01 ± 0.01 69.01 ± 0.01 68.01 ± 0.01 0.78 ± 0.01 4.07 ± 0.09
all Perceptron binary 68.50 ± 0.48 69.01 ± 0.01 70.01 ± 0.01 68.01 ± 0.01 0.78 ± 0.03 4.07 ± 0.09