Algorithm | Accuracy(%) | TP rate | FP rate | TN rate | FN rate | Sensitivity | Specificity | Precision | Fmeasure | RMSE |
---|---|---|---|---|---|---|---|---|---|---|
C4.5 | 0.6667 | 0.90 | 0.63 | 0.38 | 0.10 | 0.90 | 0.38 | 0.65 | 0.75 | 0.4683 |
Random Forest | 0.7000 | 0.79 | 0.41 | 0.59 | 0.21 | 0.79 | 0.59 | 0.71 | 0.74 | 0.4401 |
Bagging | 0.6667 | 0.68 | 0.35 | 0.65 | 0.32 | 0.68 | 0.65 | 0.72 | 0.69 | 0.4484 |
Logitboost | 0.6833 | 0.76 | 0.41 | 0.59 | 0.24 | 0.76 | 0.59 | 0.70 | 0.73 | 0.4499 |
Stacking | 0.6667 | 0.93 | 0.66 | 0.34 | 0.07 | 0.93 | 0.34 | 0.64 | 0.76 | 0.4639 |
Adaboost | 0.6611 | 0.76 | 0.46 | 0.54 | 0.24 | 0.76 | 0.54 | 0.68 | 0.71 | 0.4805 |
Multiboost | 0.7000 | 0.73 | 0.34 | 0.66 | 0.27 | 0.73 | 0.66 | 0.74 | 0.73 | 0.5187 |
Logistic | 0.6556 | 0.77 | 0.49 | 0.51 | 0.23 | 0.77 | 0.51 | 0.67 | 0.71 | 0.4362 |
Naivebayes | 0.6944 | 0.70 | 0.31 | 0.69 | 0.30 | 0.70 | 0.69 | 0.77 | 0.72 | 0.4969 |
Bayesnet | 0.6778 | 0.73 | 0.39 | 0.61 | 0.27 | 0.73 | 0.61 | 0.71 | 0.71 | 0.5232 |
Neural Network | 0.6778 | 0.66 | 0.30 | 0.70 | 0.34 | 0.66 | 0.70 | 0.73 | 0.68 | 0.4606 |
RBFnet | 0.5944 | 0.74 | 0.59 | 0.41 | 0.26 | 0.74 | 0.41 | 0.62 | 0.67 | 0.4556 |
SVM | 0.6611 | 0.71 | 0.40 | 0.60 | 0.29 | 0.71 | 0.60 | 0.71 | 0.70 | 0.5760 |