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Table 15 Bagging and boosting ensemble regressors error metrics result over NYSE dataset

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

ModelsNo. of estimatorsRMSEMAER2EVSMedAERMSLETrain timeTest time
DTBagr10.04380.03270.90240.90240.02440.02180.0040.002
SVMBagr10.04630.03580.89080.89180.02580.02280.0040.002
MLPBagr10.01350.01150.99070.99480.01110.00660.1310.003
DTBotr10.04570.03690.89370.89370.03200.02270.0040.001
SVMBotr10.04630.03580.89080.89180.02580.02280.0040.001
MLPBotr10.00890.00640.99590.99650.00480.00430.1520.001
DTBagr50.02830.02330.95910.95930.02010.01420.0110.002
SVMBagr50.04560.03540.89400.89590.02490.02240.0100.001
MLPBagr50.00830.00620.99650.99810.00480.00412.1600.002
DTBotr50.01930.01450.98100.98110.01140.00930.0120.002
SVMBotr50.04650.03610.89010.89180.02530.02280.0180.002
MLPBotr50.00700.00470.99750.99810.00320.00340.4910.002
DTBagr150.02950.02500.95550.95560.02330.01490.0290.007
SVMBagr150.04650.03610.88990.89220.02560.02280.0250.009
MLPBagr150.00880.00680.99600.99840.00550.00433.5900.020
DTBotr150.01930.01530.98100.98110.01270.00930.0930.009
SVMBotr150.04550.03540.89470.89700.02520.02230.1450.029
MLPBotr150.00750.00550.99710.99840.00420.00372.5570.007
DTBagr200.02680.02350.96340.96350.02240.01340.0360.006
SVMBagr200.04650.03610.89000.89200.02530.02280.0330.007
MLPBagr200.00910.00720.99580.99840.00570.00443.7670.011
DTBotr200.01790.01390.98370.98370.01160.00850.0410.005
SVMBotr200.04550.03540.89470.89700.02520.02230.0450.005
MLPBotr200.00760.00550.99710.99840.00410.00373.3050.009
DTBagr500.02230.01890.97470.97470.01750.01100.0840.009
SVMBagr500.04650.03610.89000.89240.02560.02280.0780.023
MLPBagr500.00940.00760.99550.99830.00650.00468.2370.022
DTBotr500.01670.01380.98580.98580.01230.00810.1110.010
SVMBotr500.04550.03540.89470.89700.02520.02230.1480.013
MLPBotr500.00790.00580.99680.99820.00440.00396.8510.014
DTBagr1000.02170.01870.97590.97590.01800.01080.1500.016
SVMBagr1000.04650.03610.89000.89240.02550.02280.1550.023
MLPBagr1000.00940.00760.99550.99840.00630.004619.7910.058
DTBotr1000.01270.01070.99180.99180.01000.00620.4240.026
SVMBotr1000.04550.03540.89470.89700.02520.02230.2910.069
MLPBotr1000.00790.00580.99680.99820.00440.00396.7880.015
DTBagr1500.02140.01880.97670.97670.01830.01050.2710.058
SVMBagr1500.04640.03610.89030.89260.02550.02270.1690.035
MLPBagr1500.00950.00770.99540.99830.00640.004624.5020.071
DTBotr1500.01180.00980.99290.99290.00870.00570.5020.044
SVMBotr1500.04550.03540.89470.89700.02520.02231.0180.174
MLPBotr1500.00790.00580.99680.99820.00440.00396.6170.015
DTBagr2000.02220.01950.97500.97500.01880.01080.8600.378
SVMBagr2000.04650.03610.89000.89250.02570.02271.0910.064
MLPBagr2000.00950.00760.99540.99830.00630.004635.9160.092
DTBotr2000.01090.00900.99390.99390.00800.00530.5210.063
SVMBotr2000.04550.03540.89470.89700.02520.02230.5450.042
MLPBotr2000.00790.00580.99680.99820.00440.00394.8470.068