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Table 1 Statistical analysis of the RP model.

From: IKKβ inhibitor identification: a multi-filter driven novel scaffold

Data set

Accuracya(%)

Sensitivityb(%)

Specificityc(%)

Precisiond(%)

Kappae

MCCf

Training

89.8 (202/225)

92.2 (95/103)

87.7(107/122)

86.3

0.97

0.8

Test

73.8 (62/84)

77(47/61)

65.2 (15/23)

85.4

0.77

0.4

  1. aAccuracy = (TP + TN)/(TP +TN + FP + FN); bSensitivity = TP/(TP + FN); cSpecificity = TN/(TN + FP); dPrecision = TP/(TP + FP); eKappa = accuracy-E/1-E, where E = expected agreement = (TN+FN) (TN+FP) (FP+TP) (FN+TP)/(TP+FP+FN+TN)2; fMCC = (TP * TN) - (FP * FN)/√(TP + FN) (TP + FP) (TN+ FP) (TN + FN).
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BMC Bioinformatics

ISSN: 1471-2105

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