Table 5.

Quad stack performance evaluation for different datasets

Rate	Dataset 1			Dataset 2			Dataset 3			Combined
	C	N	P	C	N	P	C	N	P	C	N	P
Sensitivity	0.9661	0.9650	0.9848	0.9632	0.9708	0.9148	0.9716	0.9678	0.9847	0.9652	0.9739	0.9839
Specificity	0.9991	0.9866	0.9676	0.9819	0.9539	0.9920	0.9854	0.9795	0.9886	0.9820	0.9956
F1-score	0.9785	0.9619	0.9842	0.9524	0.9743	0.9165	0.9771	0.9601	0.9864	0.9517	0.9733	0.9892
Precision	0.9913	0.9589	0.9836	0.9419	0.9779	0.9182	0.9828	0.9525	0.9882	0.9386	0.9728	0.9946
Negative predictive	0.9966	0.9886	0.9698	0.9887	0.9395	0.9917	0.9957	0.9902	0.9735	0.9937	0.9828	0.9870
Miss rate	0.0339	0.0339	0.0152	0.0368	0.0368	0.0852	0.0284	0.0284	0.0153	0.0348	0.0348	0.0161
Fall-out	0.0009	0.0134	0.0324	0.0181	0.0461	0.0080	0.0026	0.0146	0.0205	0.0114	0.0180	0.0044
False discovery	0.0087	0.0411	0.0164	0.0581	0.0221	0.0818	0.0172	0.0475	0.0118	0.0614	0.0272	0.0054
False omission	0.0034	0.0114	0.0302	0.0113	0.0605	0.0083	0.0043	0.0098	0.0265	0.0063	0.0172	0.0130