UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 4 Issue 3
March-2017
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1703021


Registration ID:
170133

Page Number

96-100

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Title

Classification of Big data Using Support Vector Machine

Abstract

In this project, support vector machine is used for classifying big data. Support vector machine is supervised learning algorithm currently used in machine learning for classifying large data sets. The original SVM algorithm was invented by Vladimir Vapnik and the current standard incarnation was proposed by Corinna Cortes and Vapnik in 1993 and published in 1995.] I will modify the linear SVM classifier to incremental, proximal approach which will be capable of retiring old data and adding new data. By combining incremental SVM with hadoop map reduce, big data can be classified.

Key Words

Vector Machine, Supervised Learning, Big Data, Hadoop, Map Reduce, Classification.

Cite This Article

"Classification of Big data Using Support Vector Machine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 3, page no.96-100, March-2017, Available :http://www.jetir.org/papers/JETIR1703021.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Classification of Big data Using Support Vector Machine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 3, page no. pp96-100, March-2017, Available at : http://www.jetir.org/papers/JETIR1703021.pdf

Publication Details

Published Paper ID: JETIR1703021
Registration ID: 170133
Published In: Volume 4 | Issue 3 | Year March-2017
DOI (Digital Object Identifier):
Page No: 96-100
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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