文章基本信息

标题：A Comparative Study of Classification Algorithms for Spam Email Data Analysis
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作者：Aman Sharma ; Suruchi Sahni
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2011
卷号：3
期号：05
页码：1890-1895
出版社：Engg Journals Publications
摘要：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.
关键词：classification accuracy; ID3; CART; ADTree; J48; WEKA.