Paper Title

Text Classification and Classifiers: A Aomparative Study

Authors

  • Payal R. Undhad
  • Dharmesh J Bhalodiya

Keywords

Text classification, KNN, Naïve bayes, Support Vector Machine, Decision Tree

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.

Article Type

Published

How To Cite

Payal R. Undhad, Dharmesh J Bhalodiya. "Text Classification and Classifiers: A Aomparative Study".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.5, Issue 2, pp.2043-2047, URL :https://rjwave.org/ijedr/papers/IJEDR1702319.pdf

Issue

Volume 5 Issue 2 

Pages. 2043-2047

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