Defining Sports Performance by Using Automated Machine Learning System
We wanted to determine whether we could use an automated machine learning system called Azure for the selection process and placement of conscript training in such a way that AI can make decisions for the right conscript training program individually. To test this, we had four separate datasets and...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/39/1/87 |
| _version_ | 1797580347850883072 |
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| author | Kalle Saastamoinen Tuomas E. Alanen Pasi Leskinen Kai Pihlainen Joona Jehkonen |
| author_facet | Kalle Saastamoinen Tuomas E. Alanen Pasi Leskinen Kai Pihlainen Joona Jehkonen |
| author_sort | Kalle Saastamoinen |
| collection | DOAJ |
| description | We wanted to determine whether we could use an automated machine learning system called Azure for the selection process and placement of conscript training in such a way that AI can make decisions for the right conscript training program individually. To test this, we had four separate datasets and access to the Microsoft Azure automated machine learning environment. According to the test sets we performed, we see that, by using an automated machine learning environment, it was possible to reach the precision level of the decisions we wanted. The main obstacle was not the used automated machine learning environment itself, but the quality of the data used for learning. We also made improvement suggestions regarding how data could be collected and what kind of data we should measure to make predictive data analysis better and be more usable in the future. |
| first_indexed | 2024-03-10T22:48:43Z |
| format | Article |
| id | doaj.art-e5cddf00e3ce49e8a450f61c5b822e0c |
| institution | Directory Open Access Journal |
| issn | 2673-4591 |
| language | English |
| last_indexed | 2024-03-10T22:48:43Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj.art-e5cddf00e3ce49e8a450f61c5b822e0c2023-11-19T10:31:23ZengMDPI AGEngineering Proceedings2673-45912023-07-013918710.3390/engproc2023039087Defining Sports Performance by Using Automated Machine Learning SystemKalle Saastamoinen0Tuomas E. Alanen1Pasi Leskinen2Kai Pihlainen3Joona Jehkonen4Department of Military Technology, National Defence University, FI-00861 Helsinki, FinlandNaval Academy, Finnish Defence Forces, FI-00191 Helsinki, FinlandNaval Academy, Finnish Defence Forces, FI-00191 Helsinki, FinlandTraining Division, Defence Command, Finnish Defence Forces, FI-00131 Helsinki, FinlandShared Service Center, Information Management, Finnish Defence Forces, FI-04401 Helsinki, FinlandWe wanted to determine whether we could use an automated machine learning system called Azure for the selection process and placement of conscript training in such a way that AI can make decisions for the right conscript training program individually. To test this, we had four separate datasets and access to the Microsoft Azure automated machine learning environment. According to the test sets we performed, we see that, by using an automated machine learning environment, it was possible to reach the precision level of the decisions we wanted. The main obstacle was not the used automated machine learning environment itself, but the quality of the data used for learning. We also made improvement suggestions regarding how data could be collected and what kind of data we should measure to make predictive data analysis better and be more usable in the future.https://www.mdpi.com/2673-4591/39/1/87healthforecastingautomateddata-analysis |
| spellingShingle | Kalle Saastamoinen Tuomas E. Alanen Pasi Leskinen Kai Pihlainen Joona Jehkonen Defining Sports Performance by Using Automated Machine Learning System Engineering Proceedings health forecasting automated data-analysis |
| title | Defining Sports Performance by Using Automated Machine Learning System |
| title_full | Defining Sports Performance by Using Automated Machine Learning System |
| title_fullStr | Defining Sports Performance by Using Automated Machine Learning System |
| title_full_unstemmed | Defining Sports Performance by Using Automated Machine Learning System |
| title_short | Defining Sports Performance by Using Automated Machine Learning System |
| title_sort | defining sports performance by using automated machine learning system |
| topic | health forecasting automated data-analysis |
| url | https://www.mdpi.com/2673-4591/39/1/87 |
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