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Table 3 Assessment of the predictive power of each single model using the 100-gene profile

From: Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

Prediction model

ACC

AUC

 

Training sample

Test sample

Δ(Difference)

Training sample

Test sample

Δ(Difference )

DT

93.63

63.45

30.18

94.02

56.90

37.13

LR

82.53

64.12

18.40

87.68

58.96

28.72

ANN80

73.42

70.93

4.09

72.11

64.09

8.02

ANN100

84.63

69.54

15.09

84.98

63.88

21.09

  1. Abbreviations: ACC, ACCuracy; AUC, Area Under the Curve; DT, Decision Tree; LR, Logistic Regression; ANN80, Artificial Neural Network using 80% resampling set (over-training prevention); ANN100, ANN using 100% resampling set (without over-training prevention).