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. 2022 Feb 5;12(2):150. doi: 10.3390/metabo12020150

Table 1.

Classifier performance and selected features used to build models for distinguishing serum-derived lipids from injured and uninjured animals. Classifier and feature selection pairs were run independently for male and female animals. Cross-validation estimates were calculated using the average area under the curve (AUC) of five random subsets and served to evaluate performance of each model on previously unseen data. When models were trained on the full dataset (all samples), AUC estimates approached unity. Features selected by two or more feature selection methods are shown in bold and were used to create the final classification models.

Classifier Feature Selection Method Sex Number of Features Cross-Validation Estimate, AUC (SD) All Samples, AUC Selected Features
Linear SVM RFE M 27 0.875 (0.133) 0.980 63, 89, 244, 258, 365, 378, 417, 453, 457, 459, 476, 497, 527, 541, 543, 551, 570, 635, 651, 788, 792, 798, 808, 857, 967, 1095, 1114,
Logistic Regression RFE M 24 0.840 (0.174) 0.992 88, 89, 183, 279, 365, 453, 457, 459, 473, 476, 486, 502, 527, 543, 551, 570, 601, 651, 652, 788, 792, 808, 1104, 1114
oPLS-DA GA M 31 0.941 (0.062) 1.000 17, 63, 161, 171, 174, 209, 278, 316, 365, 407, 494, 497, 513, 527, 531, 543, 550, 551, 567, 589, 601, 616, 621, 626, 627, 652, 745, 774, 788, 1080, 1114
oPLS-DA iPLS M 20 0.891 (0.090) 0.992 61, 101, 258, 273, 321, 346, 365, 473, 527, 543, 570, 617, 652, 851, 876, 951, 994, 998, 1008, 1095
Linear SVM RFE F 28 0.766 (0.140) 0.953 8, 10, 35, 103, 104, 282, 328, 346, 348, 349, 388, 437, 457, 460, 490, 615, 757, 780, 784, 813, 825, 874, 875, 920, 989, 1026, 1044, 1110
Logistic Regression RFE F 29 0.752 (0.120) 0.976 8, 35, 73, 81, 86, 103, 263, 282, 328, 346, 348, 388, 417, 437, 443, 455, 532, 620, 745, 757, 813, 825, 874, 875, 972, 988, 989, 1055, 1110
oPLS-DA GA F 29 0.949 (0.156) 0.993 8, 27, 103, 154, 270, 378, 387, 408, 416, 455, 477, 531, 538, 550, 620, 647, 648, 652, 669, 712, 717, 719, 774, 825, 854, 869, 1082, 1095, 1110
oPLS-DA iPLS F 24 0.880 (0.110) 0.943 27, 34, 141, 146, 149, 153, 299, 328, 381, 410, 425, 529, 590, 620, 621, 634, 675, 714, 751, 773, 842, 903, 936, 989