Table 5.

Summary of results using an ensemble of both proposals.

Ensemble Method	TP	FP	TN	FN	Sensitivity	Specificity	Accuracy
Top layer RBF SVM	4766	30	489	179	0.9638	0.9422	0.9617
Top layer C5.0	4746	24	495	199	0.9598	0.9538	0.9592
Logistic Regression WA	4708	19	500	237	0.9521	0.9634	0.9531
Top layer Naïve Bayes	4539	8	511	406	0.9179	0.9846	0.9242
Top layer Linear SVM	4441	9	510	504	0.8981	0.9827	0.9061
Top layer GBM	4426	9	510	519	0.8950	0.9827	0.9034
Top layer Random Forests	4419	7	512	526	0.8936	0.9865	0.9025
Top layer kNN ($k=9$)	4418	9	510	527	0.8934	0.9827	0.9019