Multiclass feature selection algorithms base on R-SVM

Abstract

Feature selection is an important task in machine learning. Most existing feature selection methods were designed for two-class classification problems. Multiclass feature selection algorithm is less available. R-SVM or Recursive SVM is a SVM-based embedded feature selection algorithm proposed by Zhang et al[5]. It provides the function of recursive feature selection and outperforms another similar method SVM-RFE (SVM Recursive Feature Elimination) on noisy data and has become popular in bioinformatics. But both R-SVM and SVM-RFE support only binary classification. We extend R-SVM to multi-class classification and also implement the multiclass SVM-RFE method in the workflow of R-SVM. Both methods achieve good performance applied to commonly used bioinformatics datasets.