Machine Learning Mining of Athlete Event Data
Lead Research Organisation:
University of the West of England
Department Name: Faculty of Environment and Technology
Abstract
There is now widespread recognition that it is possible to extract previously unknown knowledge from datasets using machine learning techniques. In particular, rule induction algorithms capture the structure of data in a form directly amenable to human understanding. This project will explore the utility of a form of rule induction which combines evolutionary computation with reinforcement learning to produce human-readable solutions to facilitate knowledge discovery with respect to race analyses of the British swimming team. The technique, known as the Learning Classifier System (LCS), has recently shown great potential for data mining problems. LCS, along with other machine learning approaches, will be used to explore athlete datasets provided by the collaborating coach of the British swimming team.
People |
ORCID iD |
Larry Bull (Principal Investigator) |
Publications
Description | New information can be discovered from Olympic event data through modern data mining approaches. |
Exploitation Route | Physiology and training data should be captured continuously. UK Sport are now, hopefully, more widely aware of this. |
Sectors | Leisure Activities, including Sports, Recreation and Tourism |
Description | Data gathering is more widespread within UK Sport. |
Sector | Leisure Activities, including Sports, Recreation and Tourism |
Description | UK Sport |
Organisation | UK Sport |
Country | United Kingdom |
Sector | Public |
Start Year | 2007 |