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Classification using Different Normalization Techniques in Support Vector Machine

Published on October 2013 by Priti Sudhir Patki, Vishakha V. Kelkar
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International Conference on Communication Technology
Foundation of Computer Science USA
ICCT - Number 2
October 2013
Authors: Priti Sudhir Patki, Vishakha V. Kelkar
fe3ce4ea-bc33-4a5c-ad3c-6b68f26e5fd2

Priti Sudhir Patki, Vishakha V. Kelkar . Classification using Different Normalization Techniques in Support Vector Machine. International Conference on Communication Technology. ICCT, 2 (October 2013), 4-6.

@article{
author = { Priti Sudhir Patki, Vishakha V. Kelkar },
title = { Classification using Different Normalization Techniques in Support Vector Machine },
journal = { International Conference on Communication Technology },
issue_date = { October 2013 },
volume = { ICCT },
number = { 2 },
month = { October },
year = { 2013 },
issn = 0975-8887,
pages = { 4-6 },
numpages = 3,
url = { /proceedings/icct/number2/13651-1313/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Communication Technology
%A Priti Sudhir Patki
%A Vishakha V. Kelkar
%T Classification using Different Normalization Techniques in Support Vector Machine
%J International Conference on Communication Technology
%@ 0975-8887
%V ICCT
%N 2
%P 4-6
%D 2013
%I International Journal of Computer Applications
Abstract

Classification is one of the most important tasks for different application such as text categorization, tone recognition, image classification, data classification etc. The Support Vector Machine is a popular classification technique. In this paper we have performed different normalization techniques on different datasets. These techniques help in obtaining high training accuracy for classification. The classification is performed on these datasets using SVM.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Classification Normalization Support Vector Machine Kernel Functions.