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Table 7 Summary of results for all regression datasets

From: FeatureSelect: a software for feature selection based on machine learning approaches

AL NOF ET ER ER_STD ER_CI_1 ER_CI_2 ER_P ER_TS CR CR_STD CR_CI_1 CR_CI_2 CR_P CR_TS
WCC 12.5 107.5 0.033 0.000 0.030 0.033 0.000 1.3E+ 15 0.65 0.020 0.615 0.640 0.000 2.5E+ 14
LCA 10.25 124 0.030 0.000 0.030 0.033 0.000 1274.13 0.65 0.005 0.610 0.633 0.000 916.1775
GA 14.5 53 0.033 0.000 0.035 0.035 0.000 818.640 0.57 0.015 0.515 0.598 0.001 212.5
PSO 14.00 50.5 0.033 0.000 0.033 0.033 0.000 435.880 0.56 0.045 0.520 0.583 0.001 225.3125
ACO 14.00 128.25 0.033 0.000 0.035 0.035 0.000 290.915 0.57 0.050 0.473 0.570 0.003 125.4075
ICA 13.50 53 0.033 0.000 0.035 0.035 0.000 813.673 0.60 0.005 0.578 0.588 0.000 488.6925
LA 12.50 69 0.030 0.000 0.028 0.030 0.000 565.238 0.65 0.015 0.598 0.635 0.000 379.07
HTS 12.00 70.5 0.033 0.000 0.035 0.038 0.000 406.563 0.57 0.043 0.518 0.573 0.001 145.995
FOA 9.50 136.75 0.030 0.000 0.030 0.035 0.003 403.343 0.63 0.073 0.488 0.640 0.021 276.025
DSOS 9.00 105.5 0.033 0.000 0.035 0.038 0.000 325.99 0.55 0.045 0.478 0.538 0.003 213.69
CUK 10.50 124.5 0.033 0.000 0.033 0.033 0.000 998.68 0.60 0.010 0.555 0.590 0.001 662.7475