PREDVIĐANJE TOKA KARIJERE TENISERA POMOĆU TEHNIKA ANALIZE PODATAKA
DOI:
https://doi.org/10.24867/21BE21StojadinovKljučne reči:
tenis, analiza podataka, klasterovanje, regresijaApstrakt
U ovom radu opisan je proces klasterizacije metodom k-srednjih vrednosti na osnovu izabranih fizičkih karakteristika i stilova igre tenisera. Za svaki klaster kreirana je regresiona kriva, koja ukazuje na zavisnost uspeha igrača kroz sezone. Ceo proces validiran je leave-one-out metodom. Svi koraci sistema su detaljno opisani i vizualizovani.
Reference
[1] Association of Tennis Professionals (ATP), Github
https://github.com/serve-and-volley/atp-world-tour-tennis- data.git.
[2] Association of Tennis Professionals (ATP), ATP World tour www.atpworldtour.com
[4] Miha Mlakar, Tea Tušar , “Analyzing and Predicting Peak Performance Age of Professional Tennis Players” , Jožef Stefan Institute Jamova cesta 39
SI-1000 Ljubljana, Slovenia, pp 1-4, 2017.
[3] “Peak Performance and Age Among Superathletes: Track and Field, Swimming, Baseball, Tennis, and Golf”, Richard Schulz, Christine Curnow, Jurnal of Gerontology: PSYCHOLOGICAL SCIENCES, Vol. 43, No. 5, P113 – 120, 1988.
https://github.com/serve-and-volley/atp-world-tour-tennis- data.git.
[2] Association of Tennis Professionals (ATP), ATP World tour www.atpworldtour.com
[4] Miha Mlakar, Tea Tušar , “Analyzing and Predicting Peak Performance Age of Professional Tennis Players” , Jožef Stefan Institute Jamova cesta 39
SI-1000 Ljubljana, Slovenia, pp 1-4, 2017.
[3] “Peak Performance and Age Among Superathletes: Track and Field, Swimming, Baseball, Tennis, and Golf”, Richard Schulz, Christine Curnow, Jurnal of Gerontology: PSYCHOLOGICAL SCIENCES, Vol. 43, No. 5, P113 – 120, 1988.
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Objavljeno
2023-01-08
Broj časopisa
Rubrika
Elektrotehničko i računarsko inženjerstvo
