Computer based sport talent identification
<p class="Bodytextnoindent">This paper presents the concept of the computer decision support system for talent identification in sport. In this concept the use of two methods was assumed: pattern recognition based on multicriteria optimization and machine learning supervised classifi...
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| Format: | Article |
| Language: | English |
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Nicolaus Copernicus University in Toruń
2018-06-01
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| Series: | Quality in Sport |
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| Online Access: | https://apcz.umk.pl/czasopisma/index.php/QS/article/view/17182 |
| _version_ | 1811219966777622528 |
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| author | Maciej Kaczanowski |
| author_facet | Maciej Kaczanowski |
| author_sort | Maciej Kaczanowski |
| collection | DOAJ |
| description | <p class="Bodytextnoindent">This paper presents the concept of the computer decision support system for talent identification in sport. In this concept the use of two methods was assumed: pattern recognition based on multicriteria optimization and machine learning supervised classification algorithm: decision forest. The data for sport dyscyplin patterns has obtained from publication (Santos, Dawson, Matias et al. 2014). This data also has been used to generate test data sets to research purposes. The researches were carried out in author’s application and in the cloud environment Microsoft Azure Machine Learning Studio. The results show that both methods can be used with success to talent identification in sport.</p> |
| first_indexed | 2024-04-12T07:34:37Z |
| format | Article |
| id | doaj.art-77f8adaefe1e4849b4379368b634128b |
| institution | Directory Open Access Journal |
| issn | 2450-3118 |
| language | English |
| last_indexed | 2024-04-12T07:34:37Z |
| publishDate | 2018-06-01 |
| publisher | Nicolaus Copernicus University in Toruń |
| record_format | Article |
| series | Quality in Sport |
| spelling | doaj.art-77f8adaefe1e4849b4379368b634128b2022-12-22T03:41:58ZengNicolaus Copernicus University in ToruńQuality in Sport2450-31182018-06-0134425610.12775/QS.2017.02214461Computer based sport talent identificationMaciej Kaczanowski0Instytut Systemów Informatycznych, Wydział Cybernetyki Wojskowa Akademia Techniczna, Warszawa, Polska<p class="Bodytextnoindent">This paper presents the concept of the computer decision support system for talent identification in sport. In this concept the use of two methods was assumed: pattern recognition based on multicriteria optimization and machine learning supervised classification algorithm: decision forest. The data for sport dyscyplin patterns has obtained from publication (Santos, Dawson, Matias et al. 2014). This data also has been used to generate test data sets to research purposes. The researches were carried out in author’s application and in the cloud environment Microsoft Azure Machine Learning Studio. The results show that both methods can be used with success to talent identification in sport.</p>https://apcz.umk.pl/czasopisma/index.php/QS/article/view/17182talent identification in sportmulticriteria optimizationmachine learningdata scienceidentyfikacja talentów sportowychoptymalizacja wielokryterialnauczenie maszynowenauka o danych |
| spellingShingle | Maciej Kaczanowski Computer based sport talent identification Quality in Sport talent identification in sport multicriteria optimization machine learning data science identyfikacja talentów sportowych optymalizacja wielokryterialna uczenie maszynowe nauka o danych |
| title | Computer based sport talent identification |
| title_full | Computer based sport talent identification |
| title_fullStr | Computer based sport talent identification |
| title_full_unstemmed | Computer based sport talent identification |
| title_short | Computer based sport talent identification |
| title_sort | computer based sport talent identification |
| topic | talent identification in sport multicriteria optimization machine learning data science identyfikacja talentów sportowych optymalizacja wielokryterialna uczenie maszynowe nauka o danych |
| url | https://apcz.umk.pl/czasopisma/index.php/QS/article/view/17182 |
| work_keys_str_mv | AT maciejkaczanowski computerbasedsporttalentidentification |