Overview of Machine Learning Algorithms for Solving the Spam Detection Problem

Authors

  • Yuldasheva Khurshida

Keywords:

machine learning, spam filtering, spam detection algorithms, classification framework, mathematical formulation, algorithm accuracy, research directions, spam identification, machine learning in spam filtering.

Abstract

This research focuses on addressing the challenge of spam filtering through the application of machine learning techniques. This research involved a comprehensive review of spam identification algorithms, resulting in a proposed classification framework. A detailed mathematical formulation of the algorithms is presented, accompanied by empirical results demonstrating the accuracy of their current implementations. Potential avenues for future research have been highlighted to enhance spam detection capabilities.

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Published

2024-10-30

How to Cite

Yuldasheva Khurshida. (2024). Overview of Machine Learning Algorithms for Solving the Spam Detection Problem. International Journal of Learning Development and Innovation, 1(2), 140–149. Retrieved from https://gscjournal.com/IJLDI/article/view/44

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