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Spam Filtering using SVM with different Kernel Functions

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Deepak Kumar Agarwal, Rahul Kumar
10.5120/ijca2016908395

Deepak Kumar Agarwal and Rahul Kumar. Article: Spam Filtering using SVM with different Kernel Functions. International Journal of Computer Applications 136(5):16-23, February 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Deepak Kumar Agarwal and Rahul Kumar},
	title = {Article: Spam Filtering using SVM with different Kernel Functions},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {136},
	number = {5},
	pages = {16-23},
	month = {February},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

The growing volume of unwanted bulk e-mail (also known as junk-mail or spam) has generated a need for trustworthy anti-spam filters. Now a day, many Machine learning techniques have been used which are robotically filter the junk e-mail in much unbeaten rate. In this paper, we used one of the most popular machine learning Algorithm support vector machine (SVM) with different parameters using different kernel-functions (linear, polynomial, RBF, sigmoid) are implemented on spambase-dataset. Comparison of SVM performance for all kernels (linear, polynomial, RBF, sigmoid) using different parameters (C-SVC, NU-SVC) evaluated on spambase-dataset to get best accuracy.

References

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Keywords

Spam-filtering, Support Vector Machine, Kernel-functions