Twin Support Vector Machine for Clustering

doi:10.1109/TNNLS.2014.2379930

Twin Support Vector Machine for Clustering

2015-10-01

98

PRE

AI

DOI：10.1109/TNNLS.2014.2379930

Original

Original request for help

Save

Abstract

En 中文

The twin support vector machine (TWSVM) is one of the powerful classification methods. In this brief, a TWSVM-type clustering method, called twin support vector clustering (TWSVC), is proposed. Our TWSVC includes both linear and nonlinear versions. It determines k cluster center planes by solving a series of quadratic programming problems. To make TWSVC more efficient and stable, an initialization algorithm based on the nearest neighbor graph is also suggested. The experimental results on several benchmark data sets have shown a comparable performance of our TWSVC.

Keywords:

Manifold clustering

plane-based clustering

twin support vector machine (TWSVM)

unsupervised learning

Twin Support Vector Machine for Clustering

Abstract

AI Summary

Journal

Organization