A learning-based system for predicting sport injuries
| Autor: | Wanjian Bai, Liu Guangying, Hongmei Li, Ren Zhigang, Zhongde Zhang, Hua Sun, Yu Lingxia |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
021103 operations research
lcsh:TA1-2040 Computer science Applied psychology 0211 other engineering and technologies 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Learning based 02 engineering and technology lcsh:Engineering (General). Civil engineering (General) |
| Zdroj: | MATEC Web of Conferences, Vol 189, p 10008 (2018) |
| ISSN: | 2261-236X |
| DOI: | 10.1051/matecconf/201818910008 |
| Popis: | In the big data era, learning-based techniques have attracted more and more attentions in many industry areas. The sport injury prediction is one of the most critical issues in data analysis of soccer teams.However, learning-based methods have not been widely used due to the poor data quality and computational capacity. In this paper, we propose a learning-based model to forecast sport injuries according to the data from various information systems. We first reduce the attributes that have significant impact on the injury risk by using learning-based methods.Then, we provide an algorithm based on the random forest method to prevent the over-fitting problem. We have evaluated the proposed model with the real-world data. The experimental results show that our model works efficiently and achieves low error rates. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|