A new multi-class support vector algorithm

A new multi-class support vector algorithm

Multi-class classification is an important and on-going research subject in machine learning. In this article, we propose a new support vector algorithm, called ν-K-SVCR, for multi-class classification based on ν-SVM. ν-K-SVCR has parameters that enable us to control the numbers of support vectors and margin errors effectively, which is helpful in improving the accuracy of each classifier. We g...

Multi-class support vector machines: a new approach

In this paper, we propose a new approach for solving multiclass problems with Support Vector Machines. We modify the existing technique to properly reduce the empirical error, therefore we will be ideally able to outperform the previously proposed scheme for multi-class SVMs. The proposed approach also provides solutions with a significant reduction in the number of support vectors, which is an...

Probabilistic outputs for a new multi-class Support Vector Machine

Support Vector Machines are learning paradigm originally developed on the basis of a binary classification problem with signed outputs ±1. The aim of this work is to give a probabilistic interpretation to the numerical output values into a multi-classification learning problem framework. For this purpose, a recent SV Machine, called `-SVCR, addressed to avoid the lose of information occurred in...

An Efficient Hybrid Algorithm For Multi - Class Support Vector Machines

The standard support vector machines (SVM) algorithm is originally designed for two-class classification. it has been applied to solve multi-class classification problems. Several algorithms are developed for solving a multi-class problem by SVM such as one-against-one (OAO), one-against-all (OAA), and directed acyclic graph support vector machines (DAGSVM). In this research, a hybrid algorithm...

Multi-class Support Vector Machines