Predicting the personal-best times of speed skaters using case-based reasoning
Speed skating is a form of ice skating in which the skaters race each other over a variety of standardised distances. Races take place on specialised ice-rinks and the type of track and ice conditions can have a significant impact on race-times. As race distances increase, pacing also plays an important role. In this paper we seek to extend recent work on the application of case-based reasoning to marathon-time prediction by predicting race-times for speed skaters. In particular, we propose and evaluate a number of case-based reasoning variants based on different case and feature representations to generate track-specific race predictions. We show it is possible to improve upon state-of-the-art prediction accuracy by harnessing richer case representations using shorter races and track-adjusted finish and lap-times.
© Copyright 2020 Case-Based Reasoning Research and Development. ICCBR 2020. Published by Springer. All rights reserved.
| Subjects: | |
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| Notations: | endurance sports |
| Tagging: | maschinelles Lernen |
| Published in: | Case-Based Reasoning Research and Development. ICCBR 2020 |
| Language: | English |
| Published: |
Cham
Springer
2020
|
| Series: | Lecture Notes in Computer Science, 12311 |
| Online Access: | https://doi.org/10.1007/978-3-030-58342-2_8 |
| Pages: | 112-126 |
| Document types: | book |
| Level: | advanced |