A novel method of feature selection combined with sample selection is proposed to select
discriminant features in this paper. Based on support vector machine trained on training set …

This paper proposes one method of feature selection by using Support Vector Machine. The
purpose of the proposed method is to reduce the computational complexity and increase the …

The problem of feature selection is to find a subset of features for optimal classification. A
critical part of feature selection is to rank features according to their importance for …

As a feature selection method, support vector machines-recursive feature elimination (SVM-
RFE) can remove irrelevance features but don't take redundant features into consideration …

The feature selection process can be considered a problem of global combinatorial
optimization in machine learning, which reduces the number of features, removes irrelevant …

Feature selection is a satisfactory optimization problem. Most feature selection methods did
not consider the cost of feature extraction and the automatic decision of feature subset …

One may claim that the exponential growth in the amount of data provides great
opportunities for data mining. In many real world applications, the number of sources over …

This chapter introduces an approach to class-dependent feature selection and a novel
support vector machine (SVM). The relative background and theory are presented for …

This paper demonstrates a novel criterion for both feature ranking and feature selection
using Support Vector Machines (SVMs). The method analyses the importance of feature …

A central problem in machine learning is identifying a representative set of features from
which we would construct a classification model for a particular task. This paper addresses …