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INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
(International Peer Reviewed,Refereed, Indexed, Citation Open Access Journal)
ISSN: 2321-9939 | ESTD Year: 2013

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Paper Title
Text Classification and Classifiers: A Aomparative Study
Authors
  Payal R. Undhad,  Dharmesh J Bhalodiya

Abstract
Text classification is used to organize documents in a predefined set of classes. It is very useful in Web content management, search engines; email filtering, etc. The expansion of information and power automatic classification of data and textual data gains increasingly and give high performance. In this paper some machine learning classifiers are described i.e. Naive Bayesian, KNN(K-nearest neighbor), SVM(Support Vector Machine), neural network. Which are classified the text data into pre define class. This paper surveys of text classification, process of text classification different term weighing methods and comparisons between different classification algorithms.

Keywords- Text classification, KNN, Naïve bayes, Support Vector Machine, Decision Tree
Publication Details
Unique Identification Number - IJEDR1702319
Page Number(s) - 2043-2047
Pubished in - Volume 5 | Issue 2 | June 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Payal R. Undhad,  Dharmesh J Bhalodiya,   "Text Classification and Classifiers: A Aomparative Study", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.2043-2047, June 2017, Available at :http://www.ijedr.org/papers/IJEDR1702319.pdf
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