MATHEMATICAL MODELING OF MACHINE LEARNING ALGORITHMS
Keywords:
machine learning, linear regression, logistic regression, decision trees, support vector machine (SVM), neural networks.Abstract
The article provides an overview of the main mathematical models in machine learning methods, such as linear regression, logistic regression, decision trees, support vector machine (SVM) and neural networks. The study highlights the importance of mathematical modeling for the development and application of machine learning algorithms and offers new perspectives in the field.
References
Mathematical analysis: textbook / compiled by E. P. Yartseva. - Stavropol: NCFU, 2017. - 256 p. — Text: electronic // Lan: electronic library system. — URL: https://e.lanbook.com/book/155295 (access date: 06/30/2023). — Access mode: for authorization. users.
Abdullayeva, Z. S., & Shihnazarova , G. A. (2023, April). INTELLEKTUAL TAHLIL ASOSIDA CHET TILI BILIMINI TEKSHIRISHNI MODELLASHTIRISH. In INTERNATIONAL SCIENTIFIC CONFERENCES WITH HIGHER EDUCATIONAL INSTITUTIONS (Vol. 1, No. 14.04, pp. 150-152).
Shixnazarova , G. A., & Gulyamova , D. R. (2016). Modeling of the process of examination data mining techniques in the study of English language. Computer science: problems, methodology, technologies, 900.
Abdullayeva, Z. S., & Shikhnazarova , G. A. (2023). Priority factors of the nutritional model that influence the prenatal development of the fetus. In E3S Web of Conferences (Vol. 420, p. 05011). EDP Sciences.
Абдурахмонова, Н., & Абдувахобов, Г. (2021). O ‘QUV LUG ‘ATINI TUZISHNING NAZARIY METODOLOGIK ASOSLARI. МЕЖДУНАРОДНЫЙ ЖУРНАЛ ИСКУССТВО СЛОВА, 4(6).
Abdurakhmonova, N., Shakirovich, I. A., & O‘G‘Li, K. N. S. (2022). Morphological analyzer (morfoAnalyse) Python package for Turkic language. Science and Education, 3(9), 146-156.
Ismailov, A. S., Shamsiyeva, G., & Abdurakhmonova, N. (2021). Statistical machine translation proposal for Uzbek to English. Science and Education, 2(12), 212-219.
Абдурахмонова, Н., & Бойсариева, С. (2023). TABIIY TILNI QAYTA ISHLASHDA (NLP) OKKAZIONALIZMLARNING MORFEM TAHLILI. МЕЖДУНАРОДНЫЙ ЖУРНАЛ ИСКУССТВО СЛОВА, 6(3).
Abdurakhmonova, N., Tuliyev, U., Ismailov, A., & Abduvahobo, G. (2022). UZBEK ELECTRONIC CORPUS AS A TOOL FOR LINGUISTIC ANALYSIS.
In Компьютерная обработка тюркских языков. TURKLANG 2022 (pp. 231-240).
Shamshaddinovna, A.Z., Alisherovna, S.G., Karimullaevna, K.G., & Baxtiyorovich, A.S. (2023). RATIONAL NUTRITION OF PREGNANT WOMEN IN THE PERIOD OF PRENATAL DEVELOPMENT OF THE FETUS. Web of Medicine: Journal of Medicine, Practice and Nursing, 1(3), 1-6.
Abdufattokhov, S., Ibragimova, K., & Gulyamova, D. (2021, November). The applicability of machine learning algorithms in predictive modeling for sustainable energy management. In International Conference on Forthcoming Networks and Sustainability in the IoT Era (pp. 379-391). Cham: Springer International Publishing.
Gulyamova, D. (2022, April). The Applicability of Machine Learning Algorithms in Predictive Modeling for Sustainable Energy Management. In Forthcoming Networks and Sustainability in the IoT Era: Second International Conference, FoNeS-IoT 2021, Volume 1 (Vol. 129, p. 379). Springer Nature.
