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Table 17 Bagging and boosting ensemble regressors error metrics result over GSE dataset

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

ModelsNo. of estimatorsRMSEMAER2EVSMedAERMSLETrain timeTest time
DTBagr10.0020.0010.9610.9610.0010.0020.0060.002
SVMBagr10.0100.008− 0.2170.0000.0090.0090.0050.001
MLPBagr10.0110.009− 0.713− 0.6690.0090.0110.2420.014
DTBotr10.0030.0020.8820.8820.0020.0030.0040.001
SVMBotr10.0100.008− 0.2170.0000.0090.0090.0050.001
MLPBotr10.0100.008− 0.323− 0.3230.0060.0100.1560.001
DTBagr50.0010.0010.9730.9730.0010.0010.0190.002
SVMBagr50.0100.008− 0.2170.0000.0090.0090.0220.002
MLPBagr50.0040.0030.7420.7550.0030.0040.5260.003
DTBotr50.0020.0020.9310.9310.0010.0020.0130.001
SVMBotr50.0100.008− 0.2170.0000.0090.0090.1440.011
MLPBotr50.0070.0040.4070.4080.0030.0061.9190.003
DTBagr150.0020.0010.9700.9700.0010.0010.0470.005
SVMBagr150.0100.008− 0.2160.0000.0090.0090.0450.005
MLPBagr150.0030.0020.8870.8950.0020.0031.5310.008
DTBotr150.0010.0010.9800.9800.0010.0010.0750.022
SVMBotr150.0100.008− 0.2170.0000.0090.0090.1710.013
MLPBotr150.0040.0030.8250.8290.0020.0042.2230.005
DTBagr200.0010.0010.9750.9750.9750.0010.0410.004
SVMBagr200.0100.008− 0.2200.0000.2200.0090.0290.005
MLPBagr200.0020.0010.9630.9770.9630.0022.4270.008
DTBotr200.0010.0010.9800.9800.9800.0010.0480.004
SVMBotr200.0100.008− 0.2170.0000.2170.0090.0460.005
MLPBotr200.0030.0020.8610.8700.8610.0032.9210.040
DTBagr500.0010.0010.9770.9770.0010.0010.3170.076
SVMBagr500.0100.008− 0.2160.0000.0090.0090.3760.171
MLPBagr500.0010.0010.9820.9900.0010.0018.2200.029
DTBotr500.0010.0010.9870.9870.0010.0010.1060.009
SVMBotr500.0100.008− 0.2170.0000.0090.0090.0980.015
MLPBotr500.0020.0010.9580.9650.0010.0027.2310.023
DTBagr1000.0010.0010.9750.9750.0010.0010.1820.028
SVMBagr1000.0100.008− 0.2150.0000.0090.0090.2510.039
MLPBagr1000.0010.0010.9910.9940.0010.00115.4110.054
DTBotr1000.0010.0010.9910.9910.0010.0010.6440.025
SVMBotr1000.0100.008− 0.2170.0000.0090.0090.2140.092
MLPBotr1000.0010.0010.9830.9870.0010.00114.6320.045
DTBagr1500.0010.0010.9760.9760.0010.0010.2660.027
SVMBagr1500.0100.008− 0.2120.0000.0090.0090.1810.073
MLPBagr1500.0010.0010.9940.9970.0010.00120.0290.206
DTBotr1500.0010.0010.9940.9940.0000.0010.3810.023
SVMBotr1500.0100.008− 0.2170.0000.0090.0090.2490.032
MLPBotr1500.0010.0010.9850.9890.0010.00119.3930.042
DTBagr2000.0010.0010.9740.9740.0010.0010.3930.032
SVMBagr2000.0100.008− 0.2130.0000.0090.0090.2560.048
MLPBagr2000.0010.0010.9950.9960.0010.00128.0650.238
DTBotr2000.0010.0010.9950.9950.0000.0010.7860.024
SVMBotr2000.0100.008− 0.2170.0000.0090.0090.4740.038
MLPBotr2000.0010.0010.9850.9890.0010.00126.8150.048