Improvements to Platt's SMO algorithm for SVM classifier design

Keerthi, SS and Shevade, SK and Bhattacharyya, C and Murthy, KRK (2001) Improvements to Platt's SMO algorithm for SVM classifier design. In: Neural Computation, 13 (3). pp. 637-649.

PDF fulltext.pdf - Published Version Restricted to Registered users only Download (159kB) | Request a copy

Abstract

This article points out an important source of inefficiency in Platt's sequential minimal optimization (SMO) algorithm that is caused by the use of a single threshold value. Using clues from the KKT conditions for the dual problem, two threshold parameters are employed to derive modifications of SMO. These modified algorithms perform significantly faster than the original SMO on all benchmark data sets tried.

Item Type:	Journal Article
Publication:	Neural Computation
Publisher:	MIT Press
Additional Information:	Copyright of this article belongs to MIT Press.
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	20 Aug 2009 11:52
Last Modified:	19 Sep 2010 04:55
URI:	http://eprints.iisc.ac.in/id/eprint/17038

Actions (login required)

View Item