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Table 5 Results of testing ProA-SVM and ProA-RF on the SP dataset

From: Identification of properties important to protein aggregation using feature selection

Predictor Dataset TP FN FP TN Ac MCC
ProA-SVM EUKSIG.reduc 1022 103 189 936 0.8702 0.7426
EUKANC.reduc 55 12 10 56 0.8346 0.6695
GRAM+SIG.reduc 118 51 33 136 0.7515 0.5058
GRAM-SIG.reduc 286 64 73 277 0.8043 0.6088
Total 1481 230 305 1405 0.8436 0.6879
ProA-RF EUKSIG.reduc 896 229 297 828 0.7662 0.5334
EUKANC.reduc 60 7 9 57 0.8797 0.7597
GRAM+SIG.reduc 127 42 38 131 0.7633 0.5268
GRAM-SIG.reduc 290 60 104 246 0.7657 0.5357
  Total 1373 338 448 1262 0.7702 0.5416
  1. TP: the number of True Positive samples; FN: the number of False Negative samples; FP: the number of false positive samples and TP: the number of true positive samples. Ac, Accuracy; MCC, Matthews correlation coefficient.