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Lightweight Machine Learning for Spam Detection by angelamaria2003fa is a document available to read on EtoBox.

What is Lightweight Machine Learning for Spam Detection about?

This report presents a lightweight and interpretable machine learning model for detecting spam in SMS and email communications, utilizing NLP techniques and classification algorithms. The study achieved high accuracy rates of 97.8% for SMS and 99.3% for email by employing Logistic Regression and Random Forest for SMS, and Naive Bayes for email, while also integrating Explainable AI methodologies like LIME for user understanding. The research addresses the challenges of spam detection, including high volumes

Author

angelamaria2003fa

Language

EN