Applying Decision Tree Techniques to Classify European Football Teams

Autor:	YILDIZ, Bünyamin Fuat
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Computer Science Interdisciplinary Application machine learning decision trees football classification sports ComputingMilieux_PERSONALCOMPUTING ComputerApplications_COMPUTERSINOTHERSYSTEMS Bilgisayar Bilimleri Disiplinler Arası Uygulamalar
Zdroj:	Volume: 1, Issue: 2 86-91 Journal of Soft Computing and Artificial Intelligence
ISSN:	2717-8226
Popis:	Machine learning techniques are powerful tools used in all aspects of science. However, these techniques are relatively new in sports. This study was carried out to measure the accuracy of decision trees in the classification of football teams. We applied five types of decision tree algorithms to classify elite football teams in Spain, Italy, and England to determine whether decision tree techniques are robust in classifying elite football teams. The findings show that the accuracy rate is above 77 percent for each of the decision trees. The key qualities that cause branching in decision trees may constitute a criterion for the targeting of football authorities. More research is required to determine which machine learning techniques are more efficient in classifying football teams.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=tubitakulakb::4083e7841c04dedce231950bdcda0242 https://dergipark.org.tr/tr/pub/jscai/issue/56697/817250 Zobrazit plný text záznamu