Table 4 Comparison of the accuracy of different classifiers using 2 known biomarker genes and our selection of 6 genes on Ma et al. and Loi et al. data
From: A voting approach to identify a small number of highly predictive genes using multiple classifiers
Classifier | Ma et al.data | Loi et al.data | ||
|---|---|---|---|---|
| Â | 2 genes | 6 genes | 2 genes | 6 genes |
C4.5 | 60.00% | 100% | 75.64% | 80.77% |
C4.5 with boosting (ADABoost) | 70.00% | 100% | 66.67% | 82.05% |
C4.5 with bagging | 70.00% | 100% | 67.95% | 75.64% |
Naïve Bayes | 60.00% | 100% | 74.36% | 74.36% |
Naïve Bayes with boosting | 60.00% | 80.00% | 74.36% | 77.95% |
Naïve Bayes with bagging | 60.00% | 100% | 75.64% | 75.64% |
LMT | 70.00% | 100% | 76.92% | 79.49% |
NBTree | 80.00% | 80.00% | 75.64% | 82.05% |
Random Forest | 60.00% | 100% | 74.36% | 75.38% |
Random Forest with boosting | 70.00% | 100% | 67.95% | 74.36% |
Random Forest with bagging | 70.00% | 100% | 74.36% | 71.79% |
k-NN | 70.00% | 100% | 73.08% | 71.79% |
Logistic Regression | 70.00% | 100% | 76.92% | 74.36% |
ANN | 60.00% | 100% | 74.36% | 76.67% |
SVM | 60.00% | 100% | 74.36% | 74.36% |