首页|Research Findings from Guangxi University of Science and Technology Update Under standing of Machine Learning (Analysis of Spam Classification Based on Naive Bay es and Random Forest Model)
Research Findings from Guangxi University of Science and Technology Update Under standing of Machine Learning (Analysis of Spam Classification Based on Naive Bay es and Random Forest Model)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Researchers detail new data in artificial intelli gence. According to news reporting originating from Liuzhou, People’s Republic o f China, by NewsRx correspondents, research stated, “Spam classification has bec ome more and more significant in email filtering and content auditing systems no wadays.” Our news reporters obtained a quote from the research from Guangxi University of Science and Technology: “Despite the development of many ways for filtering spa m, spammers continue to adopt new methods for spam detection, which has left us overwhelmed with spam. Furthermore, robust, and flexible categorization algorith ms are necessary to keep up with the constant evolution of spam tactics. The bes t method for categorizing and filtering spam now is to use machine learning tech niques. In this study, a large spam dataset containing 5572 email instances is u sed in simulations for the spam classification task. This study comparatively an alyzes two prevalent machine learning algorithms, namely, Random Forest and Naiv e Bayes. A detailed description of both algorithms, including their theoretical foundations and practical implementations in spam detection, is provided.”
Guangxi University of Science and TechnologyLiuzhouPeople’s Republic of ChinaAsiaAlgorithmsCyborgsEmerging T echnologiesMachine Learning
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