Table 7

Performance comparison among the configurations in the weighted classification on the test set.

Configuration f

Accuracya

Recallb

Precisionc

Specificityd

Negative Predictive Valuee


Base (not weighted)

80%

90%

82%

57%

72%

W26_74 (balanced outcome)

65%

63%

82%

70%

47%

Wl_1000 (bias poor)

66%

60%

86%

78%

47%

W1000_1 (bias good)

78%

98%

77%

35%

89%


a Accuracy is the fraction of correctly classified patients and overall classified patients.

b Recall is the fraction of correctly classified good outcome patients and the overall predicted good outcome patients.

c Precision is the fraction of correctly classified good outcome patients and the predicted good outcome patients.

d Specificity is the fraction of correctly classified poor outcome patients and the overall poor outcome patients.

e Negative predictive value is the fraction of correctly classified poor outcome patients and the overall predicted poor outcome patients.

f Configuration indicates the specific weights assigned to the outcomes in the weighted classification.

Cangelosi et al. BMC Bioinformatics 2014 15(Suppl 5):S4   doi:10.1186/1471-2105-15-S5-S4

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