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GLOBECOM
2008
IEEE
13 years 11 months ago
Support Vector Machines and Random Forests Modeling for Spam Senders Behavior Analysis
— Unwanted and malicious messages dominate Email traffic and pose a great threat to the utility of email communications. Reputation systems have been getting momentum as the sol...
Yuchun Tang, Sven Krasser, Yuanchen He, Weilai Yan...
ECRIME
2007
13 years 9 months ago
A comparison of machine learning techniques for phishing detection
There are many applications available for phishing detection. However, unlike predicting spam, there are only few studies that compare machine learning techniques in predicting ph...
Saeed Abu-Nimeh, Dario Nappa, Xinlei Wang, Suku Na...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 5 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ISCI
2007
130views more  ISCI 2007»
13 years 5 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...