Pregled bibliografske jedinice broj: 1204148
Machine learning approach to predicting a basketball game outcome
Machine learning approach to predicting a basketball game outcome // International Journal of Data Science, 7 (2022), 1; 60-77 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1204148 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Machine learning approach to predicting a
basketball game outcome
Autori
Poch Alonso, Roger ; Bagić Babac, Marina
Izvornik
International Journal of Data Science (2053-0811) 7
(2022), 1;
60-77
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
machine learning ; supervised learning ; prediction ; KNN ; k-nearest neighbours ; decision trees ; Naive Bayes classifier ; basketball ; NBA.
Sažetak
The outcome of a basketball match depends on many factors, such as the morale of a team or a player, skills, coaching strategy, and many others. Thus, it is a challenging task to predict the exact results of individual matches. This paper shows how to learn from historical data about previous basketball games, including both individual and team features, to predict future matches. It outlines the advantages and disadvantages of existing machine learning systems and tries to apply the best practices focusing on a case study of the National Basketball Association (NBA). In addition, a comparison between different machine learning algorithms in search of the most accurate prediction is provided.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Marina Bagić Babac
(autor)
Citiraj ovu publikaciju:
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