Multicategory Classification by Support Vector Machines

One-against-all multicategory classification via discrete support vector machines

Discrete support vector machines (DSVM), recently proposed in [l01 and [ l l ] for binary classification problems, have been shown to outperform other competing approaches on well-known benchmark datasets. Here we address their extension to multicategory classification, by developing a one-against-all framework in which a set of binary discrimination problems are solved by means of DSVM. Comput...

A moment inequality for multicategory support vector machines

The success of support vector machines in binary classification relies on the fact that hinge loss utilized in the risk minimization targets the Bayes rule. Recent research explores some extensions of this large margin based method to the multicategory case. We obtain a moment inequality for multicategory support vector machine loss minimizers with fast rate of convergence.

Reinforced Multicategory Support Vector Machines

Support vector machines are one of the most popular machine learning methods for classification. Despite its great success, the SVM was originally designed for binary classification. Extensions to the multicategory case are important for general classification problems. In this article, we propose a new class of multicategory hinge loss functions, namely reinforced hinge loss functions. Both th...

Class-specific Variable Selection for Multicategory Support Vector Machines

This paper proposes a class-specific variable selection method for multicategory support vector machines (MSVMs). Different from existing variable selection methods for MSVMs, the proposed method not only captures the important variables for classification, but also identifies the discriminable and non discriminable classes so as to enhance the interpretation for multicategory classification pr...

Multicategory Support Vector Machines

The Support Vector Machine (SVM) has shown great performance in practice as a classification methodology. Oftentimes multicategory problems have been treated as a series of binary problems in the SVM paradigm. Even though the SVM implements the optimal classification rule asymptotically in the binary case, solutions to a series of binary problems may not be optimal for the original multicategor...

Multicategory Support Vector Machines, Theory, and Application to the Classification of . . .