Algorithm | Accuracy(%) | TP rate | FP rate | TN rate | FN rate | Sensitivity | Specificity | Precision | Fmeasure | RMSE |
---|---|---|---|---|---|---|---|---|---|---|
C4.5 | 0.6444 | 0.99 | 0.79 | 0.21 | 0.01 | 0.99 | 0.21 | 0.61 | 0.76 | 0.4687 |
Random Forest | 0.6500 | 0.79 | 0.53 | 0.48 | 0.21 | 0.79 | 0.48 | 0.65 | 0.71 | 0.4569 |
Bagging | 0.6833 | 0.78 | 0.44 | 0.56 | 0.22 | 0.78 | 0.56 | 0.69 | 0.73 | 0.4285 |
Logitboost | 0.6889 | 0.83 | 0.49 | 0.51 | 0.17 | 0.83 | 0.51 | 0.69 | 0.75 | 0.4402 |
Stacking | 0.6444 | 0.99 | 0.79 | 0.21 | 0.01 | 0.99 | 0.21 | 0.61 | 0.76 | 0.4761 |
Adaboost | 0.6444 | 0.77 | 0.51 | 0.49 | 0.23 | 0.77 | 0.49 | 0.69 | 0.69 | 0.4412 |
Multiboost | 0.6889 | 0.81 | 0.46 | 0.54 | 0.19 | 0.81 | 0.54 | 0.70 | 0.74 | 0.5175 |
Logistic | 0.7500 | 0.79 | 0.30 | 0.70 | 0.21 | 0.79 | 0.70 | 0.78 | 0.78 | 0.4224 |
Naivebayes | 0.6833 | 0.64 | 0.26 | 0.74 | 0.36 | 0.64 | 0.74 | 0.76 | 0.68 | 0.5289 |
Bayesnet | 0.6722 | 0.63 | 0.28 | 0.73 | 0.37 | 0.63 | 0.73 | 0.74 | 0.67 | 0.5308 |
Neural Network | 0.7000 | 0.70 | 0.30 | 0.70 | 0.30 | 0.70 | 0.70 | 0.75 | 0.72 | 0.4517 |
RBFnet | 0.6722 | 0.76 | 0.44 | 0.56 | 0.24 | 0.76 | 0.56 | 0.69 | 0.71 | 0.4632 |
SVM | 0.6944 | 0.71 | 0.33 | 0.68 | 0.29 | 0.71 | 0.68 | 0.74 | 0.71 | 0.5489 |