20.500.12556/DKUM-72355 Predikcija športnih rezultatov z uporabo strojnega učenja Predicting sports results using machine learning V diplomskem delu so predstavljeni zgodovina strojnega učenja in pogosto uporabljani algoritmi, opisano je, kako so se algoritmi razvijali in kateri so bili predhodniki sedanjih. Za preizkus uspešnosti izbranih algoritmov v praktičnem delu naloge je bil razvit program, v katerem je preizkušenih nekaj najpogostejših algoritmov strojnega učenja. V ta namen so bili s programom samodejno pridobljeni podatki o tekmah, ekipah in lestvici angleške nogometne lige ter shranjeni v lokalno podatkovno bazo. Namen razvitega programa in uporabljenih algoritmov strojnega učenja je napovedovanje izidov tekem in števila doseženih golov domačega moštva. Točnost napovedi se giblje med 30 in 50 odstotki, za doseganje boljših rezultatov pa bi potrebovali kakovostnejše in obsežnejše podatke. In the thesis we present the history of machine learning and commonly used algorithms. We describe how algorithms were developed and which algorithms were predecessors to the present ones. To test the performance of selected algorithms in the practical part of the thesis, we develop a program in which we try out some of the most common algorithms in machine learning. For this purpose, we automatically acquire information about the matches, teams and rankings of the English Football League, and store them in a local database. The purpose of the developed program and the used machine learning algorithms is to predict the results of the matches and the number of goals scored by the home team. The accuracy of the forecast ranges between 30 and 50 percent. For better and more comprehensive data is needed to achieve better results. strojno učenje klasifikacija regresija napovedovanje machine learning classification regression predicting true true false Ž. Korpar Slovenski jezik Angleški jezik Diplomsko delo/naloga 2018-09-20 07:47:09 2018-11-22 14:54:46 2022-08-01 22:30:20 2019-07-11 19:16:22 2018 0 [Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.832.021(043.2) 21919254 URN:SI:UM:DK:XHZBEGKS VS_Korpar_Zan_2018.pdf VS_Korpar_Zan_2018.pdf 1 B8C5087733C7D598C88D684E2EC07884 b91845037be79c0dd795e808420aba29c89d17df43620c1593c341fbc3928805 5d44ff70-7c10-11eb-bb7a-00155d0001ca 20.500.12556/dkum/5abf9db1-83b4-46e3-a49c-7bc2dc87f360 https://dk.um.si/Dokument.php?lang=slv&id=129922 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0