Presenting a Hybrid Feature Selection Method Using Chi2 and DMNB Wrapper for E-Mail Spam Filtering

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Provided by: International Journal of Computer Science and Network Solutions (IJCSNS)
Topic: Security
Format: PDF
The growing volume of spam emails has resulted in the necessity for more accurate and efficient email classification system. In this paper the authors presenting machine learning approach for enhancing the accuracy of automatic spam detection and filtering and separating them from legitimate messages. In this regard, for reducing the error rate and increasing the efficiency, the hybrid architecture on feature selection has been used. Features used in these systems, are the body of text messages.
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