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Table 7 Summary of results for the Wisconsin Breast Cancer Dataset

From: Cooperative co-evolution for feature selection in Big Data with random feature grouping

Classifier

Accuracy (%)

Sensitivity (%)

Specificity (%)

No. of features

NB

92.79

89.15

94.96

30

NB + CCEAFS

93.15

90.09

94.96

2

NB + CCFSRFG-1

95.26

90.57

98.04

2

NB + CCFSRFG-2

94.90

91.04

97.20

6

SVM

97.72

94.81

99.44

30

SVM + CCEAFS

92.79

84.43

97.76

3

SVM + CCFSRFG-1

95.96

91.98

98.32

3

SVM + CCFSRFG-2

90.51

82.55

95.24

3

k-NN

95.43

94.34

96.08

30

k-NN + CCEAFS

92.44

89.15

94.40

3

k-NN + CCFSRFG-1

95.78

89.62

96.94

3

k-NN + CCFSRFG-2

95.25

93.40

96.36

7

J48

92.97

91.04

94.12

30

J48 + CCEAFS

91.04

82.08

96.36

1

J48 + CCFSRFG-1

94.03

89.62

96.94

2

J48 + CCFSRFG-2

94.20

92.92

94.96

5

RF

96.13

93.40

97.76

30

RF + CCEAFS

93.32

89.62

95.52

2

RF + CCFSRFG-1

94.73

91.51

96.64

2

RF + CCFSRFG-2

95.43

91.51

97.76

6

LR

94.90

94.81

94.96

30

LR + CCEAFS

92.44

88.21

94.96

2

LR + CCFSRFG-1

95.96

92.93

97.76

2

LR + CCFSRFG-2

96.49

93.40

98.32

6

  1. Italic signifies the improvements of the proposed approach over existing techniques