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. 2022 May 13;14(7):9767–9779. doi: 10.1007/s12652-022-03862-5

Table 8.

Comparison with state-of-the-arts w.r.t accuracy

Dataset Methods Classifiers
DT NB RF SVM
Self-collected IG 86.23% 88.72% 90.58% 95.32%
Chi-square test 88.56% 91.37% 92.77% 97.28%
Forward selection 92.19% 93.48% 94.88% 98.57%
Backward selection 91.24% 91.54% 92.24% 96.21%
mRMR 93.89% 95.04% 95.89% 98.88%
CFS 93.56% 94.72% 95.03% 97.83%
FCBF 92.01% 94.12% 94.39% 96.49%
GRRF 94.59% 96.54% 97.74% 99.10%
UCI IG 87.31% 91.52% 91.89% 95.64%
Chi-square test 89.78% 92.34% 93.23% 97.89%
Forward selection 92.67% 93.49% 96.18% 98.92%
Backward selection 92.05% 91.14% 94.67% 97.32%
mRMR 94.23% 96.43% 98.01% 99.03%
CFS 93.89% 95.57% 97.55% 98.47%
FCBF 92.85% 94.53% 96.45% 97.12%
GRRF 95.74% 97.54% 98.79% 99.30%