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The article examines the categories of machine learning models: ensemble methods implemented by the random forest algorithm and boosting (XGB classifier, XGB regressor); linear models (logistic regression); classifier based on deep neural networks. The results of a study of machine learning models are presented, where the “Random Forest” model obtained the best results. Graphs of the ROC curve for each considered machine learning model are constructed. Various parameter values are considered for the selected model. The best model parameters have been selected.

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Investigation of Machine Learning Models for Detecting Network Anomalies

  • 会议论文

  • 发表日期：

    2026年

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  • Svetlana Govorova,
  • Sergey Melnikov,
  • Egor Govorov,
  • Mohammad Shahid

摘要

The article examines the categories of machine learning models: ensemble methods implemented by the random forest algorithm and boosting (XGB classifier, XGB regressor); linear models (logistic regression); classifier based on deep neural networks. The results of a study of machine learning models are presented, where the “Random Forest” model obtained the best results. Graphs of the ROC curve for each considered machine learning model are constructed. Various parameter values are considered for the selected model. The best model parameters have been selected.