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Talent identification in soccer using a one-class support vector machine Cover

Talent identification in soccer using a one-class support vector machine

International Journal of Computer Science in Sport
Volume 18 (2019): Issue 3 (December 2019)
By: S. Jauhiainen,  S. Äyrämö,  H. Forsman and  J-P. Kauppi  
Open Access
|Dec 2019

Authors

S. Jauhiainen

Faculty of Information Technology, University of Jyväskylä, Finland

S. Äyrämö

Faculty of Information Technology, University of Jyväskylä, Finland

H. Forsman

Eerikkila Sports & Outdoor Resort, Training and Research Centre forFinnish Football Urheiluopistontie, Tammela

J-P. Kauppi

Faculty of Information Technology, University of Jyväskylä, Finland
DOI: https://doi.org/10.2478/ijcss-2019-0021 | Journal eISSN: 1684-4769
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Language: English
Page range: 125 - 136
Published on: Dec 16, 2019
Published by: International Association of Computer Science in Sport
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
talent identification,
anomaly detection,
one-class SVM
Related subjects:
Computer sciences,
Databases and data mining,
Computer sciences, other,
Sports and recreation,
Physical education,
Sports and recreation, other

© 2019 S. Jauhiainen, S. Äyrämö, H. Forsman, J-P. Kauppi, published by International Association of Computer Science in Sport
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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