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A machine learning-based spam email detection system using decision tree

 Department: Computer Science  
 By: usericon MIke_Tech_World  

 Project ID: 8835
   Rating:  (5.0) votes: 1
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   Price:₦5000
Abstract
This research presents the design and implementation of a machine learning-based spam email detection system using the decision tree algorithm. The aim of the system is to classify incoming emails as either spam or legitimate messages, thereby reducing the risks of fraudulent activities and enhancing secure communication. The development involved collecting and preprocessing email datasets, which were then trained using the decision tree model due to its simplicity, interpretability, and effective classification capabilities. The system was implemented with a user-friendly interface that allows users to register, log in, and test email samples for classification. The evaluation of the system demonstrated its ability to accurately detect spam emails with consistent performance, showing that decision tree-based approaches are suitable for lightweight email filtering applications. The study concludes that integrating such a system into email services can significantly minimize spam intrusion and improve user productivity. Recommendations for future improvement include expanding the dataset, exploring hybrid machine learning techniques, and providing real-time integration with popular email platforms. ...
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