Table 2 Accuracy achieved on test set by different classifiers using various subsets of our 7 genes
From: A voting approach to identify a small number of highly predictive genes using multiple classifiers
Classifier | Accuracy | Gene Combination |
|---|---|---|
C4.5 | 84.52% | TSPYL5 |
C4.5 with boosting (ADABoost.M1) | 91.67% | TSPYL5-DIAPH1-AGTPBP1 |
C4.5 with bagging | 84.52% | TSPYL5 |
Naïve Bayes | 84.52% | TSPYL5 |
Naïve Bayes with boosting | 84.52% | TSPYL5 |
Naïve Bayes with bagging | 88.69% | TSPYL5-DIAPH1-NMU |
LMT | 84.52% | TSPYL5 |
NBTree | 84.52% | TSPYL5 |
Random Forest | 84.52% | TSPYL5-DIAPH1-ASPM |
Random Forest with boosting | 84.52% | TSPYL5-DIAPH1-ASPM |
Random Forest with bagging | 88.69% | TSPYL5-DIAPH1-ASPM-NMU |
k-NN | 80.36% | TSPYL5 |
Logistic Regression | 81.55% | TSPYL5-DIAPH1-CA9 |
ANN | 77.38% | TSPYL5-CA9 |
SVM | 83.33% | TSPYL5-LIN9 |