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Table 2 Performance of the SVM using different feature subsets selected by Info Gain

From: BLProt: prediction of bioluminescent proteins based on support vector machine and relieff feature selection

Feature subset Sensitivity
(%)
Specificity
(%)
MCC Test Accuracy (%) CV
Accuracy
100 features 69.50 74.21 0.4351 72.21 74.83
200 features 76.60 75.79 0.5193 76.13 78.00
300 features 70.92 77.37 0.4821 74.62 78.33
400 features 68.09 77.89 0.4611 73.72 78.17
500 features 68.09 84.21 0.5326 77.34 78.33
All features 63.12 78.19 0.4182 71.73 75.16
  1. MCC - Matthew's correlation coefficient, CV-Cross validation