Model	Fold	IBM Dataset				Cell2cell Dataset
Model	Fold	Training Error	Testing Error	AUC	ACC	Training Error	Testing Error	AUC	ACC
Naïve Bayes	1	0.2436	0.2270	0.8135	77.30%	0.0309	0.0305	0.9665	97
	2	0.2435	0.2482	0.8149	75.20%	0.0295	0.0302	0.9671	97
	3	0.2394	0.2639	0.8156	73.60%	0.0314	0.0254	0.9667	97
	4	0.2403	0.2596	0.8181	74.00%	0.0295	0.0270	0.9681	97.3
	5	0.2423	0.2386	0.8117	76.10%	0.0312	0.0328	0.9663	96.7
	6	0.2390	0.2613	0.8166	73.90%	0.0300	0.0321	0.9691	96.8
	7	0.2440	0.2400	0.8125	76.00%	0.0318	0.0343	0.9647	96.6
	8	0.2425	0.2457	0.8123	75.40%	0.0304	0.0316	0.9679	96.8
	9	0.2447	0.2272	0.8133	77.30%	0.0312	0.0330	0.9652	96.7
	10	0.2448	0.2187	0.8106	79.10%	0.0309	0.0326	0.9677	96.7
SVM	1	0.2048	0.2033	0.8300	79.90%	0.0087	0.0072	0.9927	99
	2	0.2046	0.1836	0.8262	81.70%	0.0086	0.0084	0.9908	98.9
	3	0.2048	0.1838	0.8498	81.70%	0.0087	0.0075	0.9935	99
	4	0.1993	0.2330	0.8064	76.70%	0.0085	0.0085	0.9920	98.9
	5	0.2037	0.1925	0.8447	80.80%	0.0086	0.0082	0.9924	98.8
	6	0.2018	0.2150	0.8138	78.60%	0.0083	0.0109	0.9882	98.7
	7	0.2042	0.1945	0.8239	80.50%	0.0086	0.0079	0.9917	99
	8	0.2062	0.1831	0.8655	81.70%	0.0085	0.0092	0.9926	98.8
	9	0.2002	0.2272	0.8089	77.30%	0.0086	0.0081	0.9926	99
	10	0.2033	0.2118	0.8224	78.80%	0.0085	0.0091	0.9913	98.8
Decision Tree	1	0.0858	0.2499	0.7240	75%	0.0001	0.0120	0.9853	98.8
	2	0.0841	0.2469	0.7667	75.30%	0.0001	0.0130	0.9859	98.7
	3	0.0896	0.2298	0.7447	77%	0.0002	0.0123	0.9826	98.8
	4	0.0882	0.2795	0.7168	72.10%	0.0001	0.0124	0.9846	98.9
	5	0.0880	0.2618	0.7264	73.90%	0.0002	0.0109	0.9887	98.9
	6	0.0882	0.2684	0.6994	73.20%	0.0001	0.0110	0.9853	98.8
	7	0.0868	0.2542	0.7125	74.60%	0.0000	0.0136	0.9831	98.6
	8	0.0841	0.2641	0.7321	73.60%	0.0001	0.0117	0.9854	98.8
	9	0.0844	0.2400	0.7079	76%	0.0002	0.0127	0.9863	98.7
	10	0.0899	0.2854	0.7020	71.40%	0.0001	0.0120	0.9847	98.8