Research Article
SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier
Table 11
Comparison of classification accuracy in related literature.
| | Author | Method | Accuracy% |
| | Dermatology database | | | | Xie et al. (2005) [16] | FOut_SVM | 91.74% | | Srinivasa et al. (2006) [32] | FCM_SVM | 83.30% | | Ren et al. (2006) [33] | LDA_SVM | 72.09% | | Our Method (2014) | SVM-RFE-Taguchi | 95.38% |
| | Zoo database | | | | Xie et al. (2005) [16] | FOut_SVM | 88.24% | | He (2006) [34] | NFPH_k-modes | 92.08% | | Golzari et al. (2009) [35] | Fuzzy_AIRS | 94.96% | | Our Method (2014) | SVM-RFE-Taguchi | 97.00% |
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