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Fig. 1 | BMC Genomics

Fig. 1

From: Stable feature selection based on the ensemble L 1 -norm support vector machine for biomarker discovery

Fig. 1

Backward feature elimination for optimal subset. Backward feature elimination is performed based on our ranking criteria. SVM with an RBF kernel is used as a classifier for calculating the cross-validation score. The X- and Y-axes denote the size of the feature subset and the 10-fold cross-validation AUC score, respectively. The red circle indicates the number of features with the highest AUC score in our experiment, which is 177 features with AUC = 0.996

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BMC Genomics

ISSN: 1471-2164

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