A New Feature Selection Algorithm for Efficient Spam Filtering using Adaboost and Hashing Techniques

Khongbantabam Susila Devi    and R  Ravi

doi:10.17485/ijst/2015/v8i13/65753

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A New Feature Selection Algorithm for Efficient Spam Filtering using Adaboost and Hashing Techniques

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i13/65753

Year: 2015, Volume: 8, Issue: 13, Pages: 1-8

Original Article

A New Feature Selection Algorithm for Efficient Spam Filtering using Adaboost and Hashing Techniques

Khongbantabam Susila Devi ^1* and R. Ravi ²

¹Department of Information and Communication Engineering, Anna University, Chennai, 600 025, India; [email protected]

²Department of Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli, 627003, India

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Email spam is one of the significant issues of the today's Internet. A steady measure of the spammer attack, which brings harm to corporate and bothering individual clients. There are lots of strategies to battle against the spam mail. Being as an effective procedure, it is appreciative to experience and channel the email spam. In this paper, we proposed a new approach by utilizing, the hashing algorithm with AdaBoost technique, an AdaBoost Technique classifies the text and image values. The proposed approach essentially accelerates the procedure of Adaptive Boosting (Adaboost) by lessening the amount of information focuses. This guarantees that Adaboost can prepare productive and insignificant misfortune of precision. The result ofthe proposed system is a decreased set of delegate preparing focuses, hence diminishing the general computational complexity of preparing and expanding the speed of the training process. This is will be used for large scale application.

Keywords: Adaboost, Classification, Hashing, Spam Filtering