This project is a simple spam message classifier built using Python's Scikit-learn library. It uses a Multinomial Naive Bayes model combined with a Count Vectorizer to classify text messages as either ...

This project leverages advanced machine learning algorithms to detect and classify malicious emails, focusing on spam and phishing threats. As email threats grow more sophisticated, accurate detection ...

This paper proposes a novel approach to SMS spam detection involving five steps: preprocessing, feature extraction, feature fusion, feature selection, and classification. Our model is designed to ...

This paper proposes utilizing LLMs to address humaninduced labeling bias in spam detection and applying different prompt design methods to guide the process. In text classification, we surveyed two ...