Aman Sharma and Suruchi Sahni (2011) A Comparative Study of Classification Algorithms for Spam Email Data Analysis

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A Comparative Study of Classification Algorithms for Spam Email Data Analysis

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CONTRIBUTORS:

	Author:	Aman Sharma
	Author:	Suruchi Sahni

JOURNAL:

International Journal on Computer Science and Engineering (IJCSE), 3(5), 1690 - 1695.

YEAR:

2011

PUB TYPE:

Journal Article

SUBJECT(S):

classification accuracy, ID3, CART, ADTree, J48, WEKA

DISCIPLINE:

Computer Science

HTTP:

http://www.enggjournals.com/ijcse/doc/IJCSE11-03-05-059.pdf

LANGUAGE:

English

PUB ID:

103-489-162 (Last edited on 2011/06/17 23:58:53 GMT-6)

SPONSOR(S):

ABSTRACT:
In recent years email has become one of the fastest and most economical means of communication. However increase of email users has resulted in the dramatic increase of spam emails during the past few years. Data mining -classification algorithms are used to categorize the email as spam or non-spam. In this paper, we conducted experiment in the WEKA environment by using four algorithms namely ID3, J48, Simple CART and Alternating Decision Tree on the spam email dataset and later the four algorithms were compared in terms of classification accuracy. According to our simulation results the J48 classifier outperforms the ID3, CART and ADTree in terms of classification accuracy.

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