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Feature Selection based Classification using Naive Bayes, J48 and Support Vector Machine

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 99 - Number 16
Year of Publication: 2014
Dipali Bhosale
Roshani Ade
P. R. Deshmukh

Dipali Bhosale, Roshani Ade and P R Deshmukh. Article: Feature Selection based Classification using Naive Bayes, J48 and Support Vector Machine. International Journal of Computer Applications 99(16):14-18, August 2014. Full text available. BibTeX

	author = {Dipali Bhosale and Roshani Ade and P. R. Deshmukh},
	title = {Article: Feature Selection based Classification using Naive Bayes, J48 and Support Vector Machine},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {99},
	number = {16},
	pages = {14-18},
	month = {August},
	note = {Full text available}


One way to improve accuracy of a classifier is to use the minimum number of features. Many feature selection techniques are proposed to find out the most important features. In this paper, feature selection methods Co-relation based feature Selection, Wrapper method and Information Gain are used, before applying supervised learning based classification techniques. The results show that Support vector Machine with Information Gain and Wrapper method have the best results as compared to others tested.


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