Table 1.
The overview of RVOS.
Table 2.
The overview of VSSRFE.
Table 3.
The overview of cyclic coordinate descent method for LLSVM.
Table 4.
The characteristics of raw datasets.
Table 5.
Parameters for feature selectors and classifiers on balanced datasets.
Table 6.
Parameters for SVM-VSSRFE on raw datasets.
Fig 1.
The comparison of ACC obtained on six balanced and raw datasets.
Fig 2.
The comparison of AUC obtained on six balanced and raw datasets.
Fig 3.
The comparison of MCC obtained on six balanced and raw datasets.
Table 7.
The comparison of performance and time consumption between SVM-RFE and SVM-VSSRFE.
Table 8.
The comparison of time consumption (s) between SVM-VSSRFE and LLSVM-VSSRFE.
Fig 4.
The comparison of ACC obtained by five feature selectors.
Fig 5.
The comparison of AUC obtained by five feature selectors.
Fig 6.
The comparison of MCC obtained by five feature selectors.
Fig 7.
The comparison of ACC obtained by four common classifiers.
Fig 8.
The comparison of AUC obtained by four common classifiers.
Fig 9.
The comparison of MCC obtained by four common classifiers.
Fig 10.
The classification model evaluation.