Table 13.
Classifier/Feature selection | NB | DT | SVM | k-NN | Average | Max | |
---|---|---|---|---|---|---|---|
Chi | 88.71 | 90.32 | 87.10 | 87.10 | 88.31 | 90.32 | |
Info | 85.48 | 85.48 | 87.10 | 87.10 | 86.29 | 87.10 | |
RF | 87.10 | 85.48 | 87.10 | 87.10 | 86.70 | 87.10 | |
SU | 87.10 | 91.94 | 87.10 | 88.71 | 88.71 | 91.94 | |
α DD | 1 | 80.65 | 88.71 | 88.71 | 88.71 | 86.69 | 88.71 |
0.95 | 80.65 | 88.71 | 83.87 | 83.87 | 84.27 | 88.71 | |
0.9 | 85.48 | 91.94 | 88.71 | 88.71 | 88.71 | 91.94 | |
0.85 | 88.71 | 87.10 | 87.10 | 88.71 | 87.90 | 88.71 | |
0.80 | 85.48 | 87.10 | 87.10 | 88.71 | 87.10 | 88.71 | |
0.75 | 87.10 | 87.10 | 85.48 | 85.48 | 86.29 | 87.10 | |
0.7 | 87.10 | 90.32 | 88.71 | 87.10 | 88.31 | 90.32 |
The maximums of each column are shown in boldface, indicating the highest best classification accuracies obtained among the different feature selection methods using the identical classifiers.