Software for Text Messages Reliability Analysis Based on the Machine Learning Models Ensemble

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dc.contributor.authorShevchuk, P.
dc.contributor.authorMolchanova, M.
dc.contributor.authorMazurets, O.
dc.contributor.authorМазурець, Олександр Вікторович
dc.date.accessioned2024-12-10T18:31:31Z
dc.date.available2024-12-10T18:31:31Z
dc.date.issued2024
dc.description.abstractThe developed model is the closest to predicting the data on the labeled set, showing 4 errors out of 50 test samples, which is 92% accurate when analyzing the reliability of text messages. The implementation of the test software in the form of a website was carried out by integrating Scikit-Learn and Flask technology. It is proposed to add four different machine learning models to the ensemble — logistic regression, decision trees, gradient boosting, and random forest, on the basis of which a weighted estimate of the credibility of text messages will be formed, which is calculated as the sum of the influence coefficients of each model multiplied by the output of the corresponding classifier model.
dc.identifier.citationShevchuk P., Molchanova M., Mazurets O. Software for Text Messages Reliability Analysis Based on the Machine Learning Models Ensemble. Proceedings of IV International Scientific and Practical Conference «Innovative research and perspectives of the development of science and technology». January 29-31, 2024. Stockholm, Sweden. 2024. Pp. 347-354
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/17239
dc.language.isoen
dc.titleSoftware for Text Messages Reliability Analysis Based on the Machine Learning Models Ensemble
dc.typeСтаття
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