| DC Field | Value | Language |
|---|
| dc.contributor.author | Latyshev, A. T. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2025-06-03T13:34:10Z | - |
| dc.date.available | 2025-06-03T13:34:10Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.citation | Latyshev, A. T. Machine learning algorithms for predicting user behavior / A. T. Latyshev // Электронные системы и технологии : сборник материалов 61-й научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 21–25 апреля 2025 г. / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Д. В. Лихаческий [и др.]. – Минск, 2025. – С. 1018–1019. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/59967 | - |
| dc.description.abstract | This text is about machine learning algorithms for predicting user behavior. At the beginning, the author gives definition to user behavior prediction. After that, much attention is given to the mathematical bases, applications and limitations of each method. At the end, the author describes the advantages of using machine learning algorithms for predicting user behavior. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | user behavior prediction | en_US |
| dc.subject | machine learning | en_US |
| dc.subject | logistic regression | en_US |
| dc.subject | Random Forest | en_US |
| dc.subject | Gradient Boosting | en_US |
| dc.subject | ensemble learning | en_US |
| dc.subject | churn modeling | en_US |
| dc.subject | e-commerce analytics | en_US |
| dc.subject | predictive accuracy | en_US |
| dc.title | Machine learning algorithms for predicting user behavior | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Электронные системы и технологии : материалы 61-й конференции аспирантов, магистрантов и студентов (2025)
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