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Table 2 Test results for accuracy and time of the entire transformation dataset

From: Determining threshold value on information gain feature selection to increase speed and prediction accuracy of random forest

Dataset Number of Instance Number of Feature CBFS Best First Threshold 0,05 Treshold based on Standard Deviation
Number of Feature Accuracy Time Number of Feature Accuracy Time Number of Feature Accuracy Time
EEG Eye 14.980 14 4 77.17% 7.31 3 72.06% 4.96 10 90.14% 9.41
Cancer 569 31 12 95.68% 0.08 26 96.68% 0.10 15 94.41% 0.08
ContraceptiveMethod 1.473 9 4 51.74% 0.35 3 50.90% 0.21 4 51.74% 0.27
Dermatology 366 33 15 97.70% 0.07 32 97.35% 0.07 26 97.40% 0.07
Divorce 170 54 6 96.65% 0.02 54 97.71% 0.02 53 97.65% 0.03
Electrical Grid 10.000 14 9 85.64% 5.06 5 76.73% 2.57 7 80.85% 3.44
CNAE-9 1.080 857 28 81.16% 0.27 57 90.69% 0.76 65 90.49% 0.91
Urban Land Cover 168 148 28 87.62% 0.04 110 85.89% 0.07 65 84.64% 0.05
Epilepsy 11.500 179 119 69.51% 21.52 178 69.73% 27.93 178 69.73% 27.93
SCADI 70 206 16 85.86% 0.02 58 85.00% 0.02 58 85.00% 0.02