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. 2023 Jun 30;11:e15552. doi: 10.7717/peerj.15552

Table 4. Results of FS methods for SC-3.

Feature selection Pre process Regressor Wrapper Number of features Pearson MSE
SC-3 Ph.1
F Statis. AF Decision Tree R. Gradient B. 259 0.5990 0.2357
Mutual Info.* STPE KNeighbors R. ElasticNet 121 0.5566 0.1893
Mutual Info.* STPE KNeighbors R. Gradient B. 979 0.5443 0.1917
F Statis. STPE Decision Tree R. Lasso 404 0.5346 0.1998
SC-3 Ph.3
F Statis.* STPE LinearSVR ElasticNet 1,736 0.6733 0.1920
F Statis. STPE ElasticNet ElasticNet 1,736 0.6073 0.1973
F Statis. STPE LinearSVR ElasticNet 1,736 0.6069 0.2062
F Statis. STPE XGB Regressor Lasso 1,526 0.5693 0.2114
Mutual Info.* STPE LinearSVR Lasso 4,410 0.5576 0.2021
F Statis* STPE Ridge ElasticNet 1,736 0.5507 0.2148
F Statis.* AF KNeighbors R. ElasticNet 671 0.5455 0.1990

Note:

Number of Features column represents number of distinct features selected. An asterisk (*) indicates that the hyper-parameters were not optimized.