TL
TL;DR
The purpose of the tool is to help practitioners and researchers to build datasets that can be used for training machine learning models for spam detection.
Abstract
EMFET is an open source and flexible tool that can be used to extract a large number of features from any email corpus with emails saved in EML format. The extracted features can be categorized into three main groups: header features, payload (body) features, and attachment features. The purpose of the tool is to help practitioners and researchers to build datasets that can be used for training machine learning models for spam detection. So far, 140 features can be extracted using EMFET. EMFET is extensible and easy to use. The source code of EMFET is publicly available at GitHub (this https URL)
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Improving email spam detection using content based feature engineering approach
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Voting-based Classification for E-mail Spam Detection
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