A comprehensive evaluation of ensemble learning for stock-market prediction

Journal of Big Data

Table 21 Stacking and blending ensemble classifiers error metrics result on JSE dataset

Model	Mean	STD	RMSE	MAE	R²	Precision	Recall	AUC	Train time	Test time
STK_DSN_C	0.828	0.032	0.371	0.137	0.449	0.828	0.863	0.86	5.04	0.10
STK_SND_C	0.818	0.027	0.291	0.085	0.660	0.911	0.915	0.91	267.23	10.58
STK_DNS_C	0.818	0.027	0.291	0.085	0.660	0.911	0.915	0.91	269.21	9.17
Vote(DSN)	0.827	0.028	0.348	0.121	0.513	0.838	0.879	0.87	314.04	10.51
BLD_DSN_C	0.799	0.112	0.403	0.162	0.348	0.816	0.838	0.83	21.97	2.74
BLD_SND_C	0.817	0.034	0.412	0.169	0.320	0.786	0.831	0.82	480.04	14.78
BLD_DNS_C	0.822	0.029	0.314	0.098	0.605	0.876	0.902	0.90	477.11	14.78