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Table 12 Bagging ensemble classifiers accuracy and error metrics result on NYSE dataset

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

ModelsNo. of estimatorsMeanSTDRMSEMAER2PrecisionRecallAUCTrain timeTest time
DTBagc:11.0000.0000.0000.0001.0001.0001.0001.000.0950.009
SVMBagc:10.9800.0150.1790.0320.8710.9820.9680.970.1120.006
MLPBagc:10.9970.0050.0000.0001.0001.0001.0001.000.5670.060
DTBagc:51.0000.0000.0000.0001.0001.0001.0001.000.2430.023
SVMBagc:50.9830.0130.1150.0130.9470.9860.9870.990.4700.018
MLPBagc:50.9990.0020.0000.0001.0001.0001.0001.002.2930.266
DTBagc:101.0000.0000.0000.0001.0001.0001.0001.000.2990.035
SVMBagc:100.9860.0100.1510.0230.9090.9720.9770.980.9680.036
MLPBagc:101.0000.0000.0000.0001.0001.0001.0001.006.3610.579
DTBagc:151.0000.0000.0000.0001.0001.0001.0001.000.4040.075
SVMBagc:150.9860.0080.1630.0270.8940.9650.9730.971.7320.061
MLPBagc:151.0000.0000.0000.0001.0001.0001.0001.0011.3620.678
DTBagc:201.0000.0000.0000.0001.0001.0001.0001.000.5970.104
SVMBagc:200.9870.0090.1570.0250.9010.9720.9750.981.7620.111
MLPBagc:201.0000.0000.0000.0001.0001.0001.0001.0011.6131.274
DTBagc:501.0000.0000.0000.0001.0001.0001.0001.002.9971.037
SVMBagc:500.9870.0090.1630.0270.8940.9680.9730.9710.9420.487
MLPBagc:501.0000.0000.0000.0001.0001.0001.0001.0085.5968.087
DTBagc:1001.0000.0000.0000.0001.0001.0001.0001.009.9730.798
SVMBagc:1000.9890.0070.1630.0270.8940.9680.9730.9732.8171.042
MLPBagc:1001.0000.0000.0000.0001.0001.0001.0001.00207.09817.046
DTBagc:1501.0000.0000.0000.0001.0001.0001.0001.0013.1231.343
SVMBagc:1500.9880.0100.1690.0280.8860.9680.9720.9746.7073.002
MLPBagc:1501.0000.0000.0000.0001.0001.0001.0001.00300.78934.477
DTBagc:2001.0000.0000.0000.0001.0001.0001.0001.0018.4371.691
SVMBagc:2000.9880.0100.1740.0300.8780.9650.9700.9766.9543.035
MLPBagc:2001.0000.0000.0000.0001.0001.0001.0001.00442.95330.594