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 6 Boosting Ensemble Classifiers training time, prediction 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	Train time	Test time
DTBotc	1	0.863	0.031	0.274	0.075	0.673	0.946	0.925	0.920	0.052	0.005
SVMBotc	1	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	0.313	0.009
MLPBotc	1	0.829	0.073	0.356	0.127	0.450	0.868	0.873	0.845	0.046	0.003
DTBotc	5	0.859	0.027	0.166	0.027	0.881	0.964	0.973	0.964	0.249	0.015
SVMBotc	5	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.413	0.020
MLPBotc	5	0.826	0.075	0.375	0.140	0.390	0.880	0.860	0.842	0.130	0.025
DTBotc	10	0.873	0.024	0.000	0.000	1.000	1.000	1.000	1.000	0.670	0.041
SVMBotc	10	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.358	0.017
MLPBotc	10	0.857	0.041	0.321	0.103	0.554	0.894	0.897	0.876	0.298	0.023
DTBotc	15	0.873	0.024	0.000	0.000	1.000	1.000	1.000	1.000	0.670	0.041
SVMBotc	15	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.358	0.017
MLPBotc	15	0.857	0.041	0.321	0.103	0.554	0.894	0.897	0.876	0.298	0.023
DTBotc	20	0.891	0.027	0.000	0.000	1.000	1.000	1.000	1.000	0.810	0.079
SVMBotc	20	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.333	0.019
MLPBotc	20	0.853	0.054	0.336	0.113	0.509	0.881	0.887	0.862	0.262	0.008
DTBotc	50	0.891	0.016	0.000	0.000	1.000	1.000	1.000	1.000	1.918	0.153
SVMBotc	50	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.369	0.028
MLPBotc	50	0.851	0.019	0.351	0.123	0.465	0.865	0.877	0.845	0.224	0.013
DTBotc	100	0.895	0.020	0.000	0.000	1.000	1.000	1.000	1.000	5.138	0.344
SVMBotc	100	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.628	0.021
MLPBotc	100	0.860	0.035	0.370	0.137	0.405	0.911	0.863	0.860	0.352	0.012
DTBotc	150	0.894	0.022	0.000	0.000	1.000	1.000	1.000	1.000	7.222	0.614
SVMBotc	150	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.724	0.022
MLPBotc	150	0.842	0.043	0.356	0.127	0.450	0.871	0.873	0.847	0.435	0.014
DTBotc	200	0.895	0.026	0.000	0.000	1.000	1.000	1.000	1.000	9.392	0.731
SVMBotc	200	0.613	0.037	0.600	0.360	− 0.561	0.640	0.640	0.500	1.636	0.021
MLPBotc	200	0.835	0.028	0.375	0.140	0.390	0.876	0.860	0.840	0.376	0.023

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