The 2nu-SVM: A Cost-Sensitive Extension of the nu-SVM

Date
2005-12-01
Journal Title
Journal ISSN
Volume Title
Publisher
Description
Tech Report
Abstract

Standard classification algorithms aim to minimize the probability of making an incorrect classification. In many important applications, however, some kinds of errors are more important than others. In this report we review cost-sensitive extensions of standard support vector machines (SVMs). In particular, we describe cost-sensitive extensions of the C-SVM and the nu-SVM, which we denote the 2C-SVM and 2nu-SVM respectively. The C-SVM and the nu-SVM are known to be closely related, and we prove that the 2C-SVM and 2nu-SVM share a similar relationship. This demonstrates that the 2C-SVM and 2nu-SVM explore the same space of possible classifiers, and gives us a clear understanding of the parameter space for both versions.

Description
Tech Report
Advisor
Degree
Type
Report
Keywords
Citation

M. A. Davenport, "The 2nu-SVM: A Cost-Sensitive Extension of the nu-SVM," Rice University ECE Technical Report, no. TREE 0504, 2005.

Has part(s)
Forms part of
Published Version
Rights
Link to license
Citable link to this page