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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