USING MACHINE LEARNING TO FILTER SPAM CONTENT

Verezubova N., Sakovich N., Chekulaev A.

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.