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

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

ModelMeanSTDRMSEMAER2PrecisionRecallAUCTrain timeTest time
STK_DSN_C0.8280.0320.3710.1370.4490.8280.8630.865.040.10
STK_SND_C0.8180.0270.2910.0850.6600.9110.9150.91267.2310.58
STK_DNS_C0.8180.0270.2910.0850.6600.9110.9150.91269.219.17
Vote(DSN)0.8270.0280.3480.1210.5130.8380.8790.87314.0410.51
BLD_DSN_C0.7990.1120.4030.1620.3480.8160.8380.8321.972.74
BLD_SND_C0.8170.0340.4120.1690.3200.7860.8310.82480.0414.78
BLD_DNS_C0.8220.0290.3140.0980.6050.8760.9020.90477.1114.78