Reduced support vector machine based on k-mode clustering for classification large categorical dataset

Santi Wulan Purnami*, Jasni Mohamad Zain, Abdullah Embong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The smooth support vector machine (SSVM) is one of the promising algorithms for classification problems. However, it is restricted to work well on a small to moderate dataset. There exist computational difficulties when we use SSVM with non linear kernel to deal with large dataset. Based on SSVM, the reduced support vector machine (RSVM) was proposed to solve these difficulties using a randomly selected subset of data to obtain a nonlinear separating surface. In this paper, we propose an alternative algorithm, k-mode RSVM (KMO-RSVM) that combines RSVM with k-mode clustering technique to handle classification problems on categorical large dataset. In our experiments, we tested the effectiveness of KMO-RSVM on four public available dataset. It turns out that KMO-RSVM can improve speed of running time significantly than SSVM and still obtained a high accuracy. Comparison with RSVM indicates that KMO-RSVM is faster, gets smaller reduced set and comparable testing accuracy than RSVM.

Original languageEnglish
Title of host publicationSoftware Engineering and Computer Systems - Second International Conference, ICSECS 2011, Proceedings
Pages694-702
Number of pages9
EditionPART 2
DOIs
Publication statusPublished - 2011
Event2nd International Conference on Software Engineering and Computer Systems, ICSECS 2011 - Kuantan, Malaysia
Duration: 27 Jun 201129 Jun 2011

Publication series

NameCommunications in Computer and Information Science
NumberPART 2
Volume180 CCIS
ISSN (Print)1865-0929

Conference

Conference2nd International Conference on Software Engineering and Computer Systems, ICSECS 2011
Country/TerritoryMalaysia
CityKuantan
Period27/06/1129/06/11

Keywords

  • k-mode clustering
  • large categorical dataset
  • reduced support vector machine
  • smooth support vector machine

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