Open AccessПрогнозирование результатов игры в баскетбол с использованием алгоритмов глубокого обучения
Author(s) -
A.M. Alimkhan
Publication year - 2022
Publication title -
international journal of information and communication technologies
Language(s) - English
Resource type - Journals
eISSN - 2708-2040
pISSN - 2708-2032
DOI - 10.54309/ijict.2022.2.6.015
Subject(s) - computer science , support vector machine , k nearest neighbors algorithm , linear regression , base (topology) , regression analysis , regression , data mining , artificial intelligence , econometrics , machine learning , statistics , mathematics , mathematical analysis
With the development of information technology and an ever-expanding statistical base, the possibilities for forecasting are expanding, and the dependencies of the calculated indicators on the result are considered. In this article we compare 3 most widely spread game result prediction models, and namely, Support Vector Regression, K-Nearest Neighbor model and the Linear Regression model in terms of their prediction accuracy and experimentally demonstrate the advantages of the latter.