Matches in SemOpenAlex for { <https://semopenalex.org/work/W3212109430> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W3212109430 endingPage "244" @default.
- W3212109430 startingPage "232" @default.
- W3212109430 abstract "It has been very important to understand the change of multivariable systems to make predictions accordingly. The goal of supervised machine learning is to build a model of changing classes of observations depending on various variables and to make predictions about the coming situations. Due to the fact that sports are followed by the whole world modelling sports events and studies about predicting the results of future matches have gained importance. In this study, match statistics of the teams in the Turkey Super League were used, and it was examined how successfully the outcome of the match was predicted using a decision tree, random forest, k-nearest neighbor, naive Bayes, support vector machine. According to the tests done in Turkey Super League, the support vector machine performs the best." @default.
- W3212109430 created "2021-11-22" @default.
- W3212109430 creator A5042612966 @default.
- W3212109430 creator A5078658866 @default.
- W3212109430 date "2021-12-01" @default.
- W3212109430 modified "2023-10-10" @default.
- W3212109430 title "Modelling Sport Events with Supervised Machine Learning" @default.
- W3212109430 cites W1980702505 @default.
- W3212109430 cites W1986134386 @default.
- W3212109430 cites W1989661440 @default.
- W3212109430 cites W1996031526 @default.
- W3212109430 cites W1999835727 @default.
- W3212109430 cites W2008974608 @default.
- W3212109430 cites W2035378550 @default.
- W3212109430 cites W2091344421 @default.
- W3212109430 cites W2109802089 @default.
- W3212109430 cites W2119387367 @default.
- W3212109430 cites W2122111042 @default.
- W3212109430 cites W2131329453 @default.
- W3212109430 cites W2136744117 @default.
- W3212109430 cites W2141752002 @default.
- W3212109430 cites W2142827986 @default.
- W3212109430 cites W2170428988 @default.
- W3212109430 cites W2172229041 @default.
- W3212109430 cites W2552378445 @default.
- W3212109430 cites W2567628451 @default.
- W3212109430 cites W2593372848 @default.
- W3212109430 cites W2756291343 @default.
- W3212109430 cites W2911964244 @default.
- W3212109430 cites W2915998242 @default.
- W3212109430 cites W4242807147 @default.
- W3212109430 doi "https://doi.org/10.33401/fujma.951665" @default.
- W3212109430 hasPublicationYear "2021" @default.
- W3212109430 type Work @default.
- W3212109430 sameAs 3212109430 @default.
- W3212109430 citedByCount "0" @default.
- W3212109430 crossrefType "journal-article" @default.
- W3212109430 hasAuthorship W3212109430A5042612966 @default.
- W3212109430 hasAuthorship W3212109430A5078658866 @default.
- W3212109430 hasBestOaLocation W32121094301 @default.
- W3212109430 hasConcept C117312493 @default.
- W3212109430 hasConcept C119857082 @default.
- W3212109430 hasConcept C121332964 @default.
- W3212109430 hasConcept C12267149 @default.
- W3212109430 hasConcept C127413603 @default.
- W3212109430 hasConcept C1276947 @default.
- W3212109430 hasConcept C133731056 @default.
- W3212109430 hasConcept C144237770 @default.
- W3212109430 hasConcept C148220186 @default.
- W3212109430 hasConcept C154945302 @default.
- W3212109430 hasConcept C169258074 @default.
- W3212109430 hasConcept C207456731 @default.
- W3212109430 hasConcept C33923547 @default.
- W3212109430 hasConcept C41008148 @default.
- W3212109430 hasConcept C52001869 @default.
- W3212109430 hasConcept C84525736 @default.
- W3212109430 hasConceptScore W3212109430C117312493 @default.
- W3212109430 hasConceptScore W3212109430C119857082 @default.
- W3212109430 hasConceptScore W3212109430C121332964 @default.
- W3212109430 hasConceptScore W3212109430C12267149 @default.
- W3212109430 hasConceptScore W3212109430C127413603 @default.
- W3212109430 hasConceptScore W3212109430C1276947 @default.
- W3212109430 hasConceptScore W3212109430C133731056 @default.
- W3212109430 hasConceptScore W3212109430C144237770 @default.
- W3212109430 hasConceptScore W3212109430C148220186 @default.
- W3212109430 hasConceptScore W3212109430C154945302 @default.
- W3212109430 hasConceptScore W3212109430C169258074 @default.
- W3212109430 hasConceptScore W3212109430C207456731 @default.
- W3212109430 hasConceptScore W3212109430C33923547 @default.
- W3212109430 hasConceptScore W3212109430C41008148 @default.
- W3212109430 hasConceptScore W3212109430C52001869 @default.
- W3212109430 hasConceptScore W3212109430C84525736 @default.
- W3212109430 hasIssue "4" @default.
- W3212109430 hasLocation W32121094301 @default.
- W3212109430 hasLocation W32121094302 @default.
- W3212109430 hasOpenAccess W3212109430 @default.
- W3212109430 hasPrimaryLocation W32121094301 @default.
- W3212109430 hasRelatedWork W2985924212 @default.
- W3212109430 hasRelatedWork W3117170030 @default.
- W3212109430 hasRelatedWork W4200057378 @default.
- W3212109430 hasRelatedWork W4285407528 @default.
- W3212109430 hasRelatedWork W4308191010 @default.
- W3212109430 hasRelatedWork W4313070894 @default.
- W3212109430 hasRelatedWork W4321636153 @default.
- W3212109430 hasRelatedWork W4377964522 @default.
- W3212109430 hasRelatedWork W4383746529 @default.
- W3212109430 hasRelatedWork W4384345534 @default.
- W3212109430 hasVolume "4" @default.
- W3212109430 isParatext "false" @default.
- W3212109430 isRetracted "false" @default.
- W3212109430 magId "3212109430" @default.
- W3212109430 workType "article" @default.