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USING MACHINE LEARNING TO FILTER SPAM CONTENT

Verezubova N.   (Candidate of economic sciences, associate professor Moscow State Academy of Veterinary Medicine and Biotechnology named after K.I. Scriabin )

Sakovich N.   (Doctor of technical sciences, associate professor Bryansk State Agrarian University )

Chekulaev A.   (Moscow State Academy of Veterinary Medicine and Biotechnology named after K.I. Scriabin )

The article examines the effectiveness of the Random Forest machine learning method for classifying and filtering spam content. The study demonstrates the process of training a model on a labeled text corpus, the features of data preprocessing, and the extraction of significant features. The study includes training and measuring the model, as well as interpreting the results using metrics, including those reflecting accuracy on unbalanced data.

Keywords:random forest, machine learning, spam content, information security.
 

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Citation link:
Verezubova N. , Sakovich N. , Chekulaev A. USING MACHINE LEARNING TO FILTER SPAM CONTENT // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№04/2. -С. 49-51 DOI 10.37882/2223-2966.2025.04-2.05
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