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Supporting athlete selection and strategic planning in track cycling omnium: A statistical and machine learning approach

Ofoghi, Bahadorreza, Zeleznikow, John, MacMahon, Clare and Dwyer, Dan (2013) Supporting athlete selection and strategic planning in track cycling omnium: A statistical and machine learning approach. Information Sciences, 233. pp. 200-213. ISSN 0020-0255

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Abstract

We demonstrated an in-depth data analytical process to facilitate the decision-making procedure in track cycling omnium that includes utilization of statistical, machine learning-based, and probabilistic approaches. We considered both interomnium and intra-omnium procedures.

Item Type: Article
Uncontrolled Keywords: ResPubID26708, Leave-One-Out Cross-Validation, LOOCV, decision support, track cycling omnium, statistical analysis, decision support, Bayesian network, machine learning
Subjects: FOR Classification > 0801 Artificial Intelligence and Image Processing
FOR Classification > 1106 Human Movement and Sports Science
Faculty/School/Research Centre/Department > School of Management and Information Systems
Faculty/School/Research Centre/Department > Institute of Sport, Exercise and Active Living (ISEAL)
Faculty/School/Research Centre/Department > College of Sports and Exercise Science
Depositing User: Yimin Zeng
Date Deposited: 17 Oct 2013 04:21
Last Modified: 14 Jan 2015 05:34
URI: http://vuir.vu.edu.au/id/eprint/22254
DOI: https://doi.org/10.1016/j.ins.2012.12.050
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Citations in Scopus: 7 - View on Scopus

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