This project targets the domain of e-mail spam filtering using machine learning. A classifier is trained using supervised Machine Learning algorithm called Support Vector Machine (SVM) to filter e-mail as spam or not spam. Each e-mail is converted to a feature vector. The SVM is trained on Raspberry Pi and the result displayed on the piTFT screen. In addition to displaying whether the e-mail is spam or not, the display also gives the user information about potential reasons for why the e-mail has been classified as spam. The database used for training is a toned-down version of the SpamAssassin Public Corpus; only the body of the e-mail is used.
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