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Support vector machines for spam categorization | IEEE Journals & Magazine | IEEE Xplore

Support vector machines for spam categorization


Abstract:

We study the use of support vector machines (SVM) in classifying e-mail as spam or nonspam by comparing it to three other classification algorithms: Ripper, Rocchio, and ...Show More

Abstract:

We study the use of support vector machines (SVM) in classifying e-mail as spam or nonspam by comparing it to three other classification algorithms: Ripper, Rocchio, and boosting decision trees. These four algorithms were tested on two different data sets: one data set where the number of features were constrained to the 1000 best features and another data set where the dimensionality was over 7000. SVM performed best when using binary features. For both data sets, boosting trees and SVM had acceptable test performance in terms of accuracy and speed. However, SVM had significantly less training time.
Published in: IEEE Transactions on Neural Networks ( Volume: 10, Issue: 5, September 1999)
Page(s): 1048 - 1054
Date of Publication: 30 September 1999

ISSN Information:

PubMed ID: 18252607

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