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Table 5 Comparison among discretization algorithms' performance.

From: Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients

Algorithmf

Accuracya

Recallb

Precisionc

Specificityd

NPVe

ADID

80%

90%

82%

57%

72%

EntMDL

68%

60%

91%

87%

50%

Modified Chi2

71%

64%

91%

87%

53%

ROC-based

77%

84%

82%

61%

64%

Equal Frequency

68%

60%

91%

87%

50%

  1. a Accuracy is the fraction of correctly classified patients and overall classified patients.
  2. b Recall is the fraction of correctly classified good outcome patients and the overall predicted good outcome patients.
  3. c Precision is the fraction of correctly classified good outcome patients and the predicted good outcome patients.
  4. d Specificity is the fraction of correctly classified poor outcome patients and the overall poor outcome patients.
  5. e NPV(negative predictive value) is the fraction of correctly classified poor outcome patients and the overall predicted poor outcome patients.
  6. f Discretization algorithms utilized for comparison/