A comprehensive evaluation of ensemble learning for stock-market prediction

Nti, Isaac Kofi; Adekoya, Adebayo Felix; Weyori, Benjamin Asubam

doi:10.1186/s40537-020-00299-5

Journal of Big Data

Table 10 Bagging ensemble classifiers training time, predicting time and error metrics result on GSE dataset

From: A comprehensive evaluation of ensemble learning for stock-market prediction

Models	No. estimators	Mean	STD	RMSE	MAE	R²	Precision	Recall	AUC	Training time	Testing time
DTBagc:	1	0.857	0.035	0.255	0.065	0.717	0.938	0.935	0.924	0.084	0.009
SVMBagc:	1	0.862	0.039	0.321	0.103	0.554	0.879	0.897	0.868	0.106	0.004
MLPBagc:	1	0.957	0.036	0.227	0.051	0.777	0.957	0.949	0.943	2.080	0.116
DTBagc:	5	0.881	0.020	0.166	0.027	0.881	0.969	0.973	0.966	0.202	0.024
SVMBagc:	5	0.859	0.036	0.346	0.120	0.480	0.862	0.880	0.846	0.412	0.016
MLPBagc:	5	0.972	0.019	0.203	0.041	0.822	0.953	0.959	0.949	12.505	0.652
DTBagc:	10	0.882	0.016	0.131	0.017	0.926	0.979	0.983	0.978	0.404	0.045
SVMBagc:	10	0.862	0.034	0.321	0.103	0.554	0.876	0.897	0.865	0.804	0.048
MLPBagc:	10	0.978	0.020	0.131	0.017	0.926	0.979	0.983	0.978	22.697	1.823
DTBagc:	15	0.878	0.025	0.117	0.014	0.941	0.984	0.986	0.983	0.537	0.050
SVMBagc:	15	0.863	0.034	0.331	0.110	0.524	0.867	0.890	0.856	1.132	0.043
MLPBagc:	15	0.984	0.017	0.117	0.014	0.941	0.989	0.986	0.985	37.923	2.578
DTBagc:	20	0.881	0.020	0.083	0.007	0.970	0.995	0.993	0.993	0.789	0.087
SVMBagc:	20	0.863	0.035	0.336	0.113	0.509	0.867	0.887	0.853	1.872	0.059
MLPBagc:	20	0.982	0.018	0.143	0.021	0.911	0.979	0.979	0.976	55.596	3.145
DTBagc:	50	0.897	0.011	0.000	0.000	1.000	1.000	1.000	1.000	1.927	0.139
SVMBagc:	50	0.863	0.038	0.336	0.113	0.509	0.860	0.887	0.849	3.913	0.143
MLPBagc:	50	0.971	0.022	0.117	0.014	0.941	0.984	0.986	0.983	144.367	7.525
DTBagc:	100	0.893	0.016	0.000	0.000	1.000	1.000	1.000	1.000	3.267	0.240
SVMBagc:	100	0.862	0.035	0.331	0.110	0.524	0.860	0.890	0.852	10.105	0.367
MLPBagc:	100	0.976	0.016	0.083	0.007	0.970	0.995	0.993	0.993	308.796	16.173
DTBagc:	150	0.894	0.014	0.000	0.000	1.000	1.000	1.000	1.000	5.475	0.378
SVMBagc:	150	0.860	0.034	0.331	0.110	0.524	0.864	0.890	0.854	15.336	0.461
MLPBagc:	150	0.975	0.016	0.101	0.010	0.955	0.989	0.990	0.988	430.847	23.734
DTBagc:	200	0.888	0.017	0.000	0.000	1.000	1.000	1.000	1.000	6.641	0.495
SVMBagc:	200	0.862	0.037	0.336	0.113	0.509	0.863	0.887	0.851	18.557	0.688
MLPBagc:	200	0.969	0.022	0.083	0.007	0.970	0.989	0.993	0.990	536.433	34.095

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