Prediction method Reference   tp fn fp tn MCC  ACC(%)
Expectation Maximization and Support Vector Machine(EMSVM) This paper   52 1 0 53 0.98 99.05
Knowledge Based Neural Network(KBANN) Geoffrey G. Towel1 et al.
(1990)    
- - - - - 96.22
Multilayer Perceptron - - - - - 92.45
OťNeill’s Method - - - - - 88.68
K-Nearest Neighbors(k-NN) - - - - - 87.74
Decision Tree (ID3) - - - - - 82.08
Hidden Markov Model(HMM) Leonardo G. Tavares et al
.(2008)      
50 3 5 48 0.850 92.45
Complement Class Naive Bayes(CNB) 49 4 3 50 0.868 93.40
Multilayer Perceptron Neural Network(MLP) 49 4 3 50 0.968 93.40
Support Vector Machine(SVM) 49 4 4 49 0.849 92.45
LogitBoost 47 6 5 48 0.793 89.62
NBTree 47 6 5 48 0.793 89.62
Lazy Bayesian Rules Classifier(LBR) 48 5 3 50 0.850 92.45
PART 44 9 11 42 0.623 81.13
ANN trained with backpropagation Raúl Ramos-Pollán et al.
(2012)    
- - - - - 89.09
ANN trained with resilient propagation - - - - - 94.36
ANN trained with simulated annealing - - - - - 88.50
ANN trained with genetic algorithms - - - - - 73.37
Table 3: Comparison between our method and other reported methods.