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Machine Learning and Data Mining for...
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Davis, Jesse.
Machine Learning and Data Mining for Sports Analytics = 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Machine Learning and Data Mining for Sports Analytics/ edited by Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann.
其他題名:
7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings /
其他作者:
Zimmermann, Albrecht.
面頁冊數:
X, 141 p. 6 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Computer Communication Networks. -
電子資源:
https://doi.org/10.1007/978-3-030-64912-8
ISBN:
9783030649128
Machine Learning and Data Mining for Sports Analytics = 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings /
Machine Learning and Data Mining for Sports Analytics
7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings /[electronic resource] :edited by Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann. - 1st ed. 2020. - X, 141 p. 6 illus.online resource. - Communications in Computer and Information Science,13241865-0929 ;. - Communications in Computer and Information Science,498.
Routine Inspection: A playbook for corner kicks -- How data availability aects the ability to learngood xG models -- Low-cost optical tracking of soccer players -- An Autoencoder Based Approach to SimulateSports Games -- Physical performance optimization in football -- Predicting Player Trajectoriesin Shot Situations in Soccer -- Stats Aren't Everything: Learning Strengths andWeaknesses of Cricket Players -- Prediction of tiers in the rankingof ice hockey players -- A Machine Learning Approach for Road CyclingRace Performance Prediction -- Mining Marathon Training Data to GenerateUseful User Proles -- Learning from partially labeled sequences forbehavioral signal annotation.
This book constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.
ISBN: 9783030649128
Standard No.: 10.1007/978-3-030-64912-8doiSubjects--Topical Terms:
669310
Computer Communication Networks.
LC Class. No.: Q334-342
Dewey Class. No.: 006.3
Machine Learning and Data Mining for Sports Analytics = 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings /
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Routine Inspection: A playbook for corner kicks -- How data availability aects the ability to learngood xG models -- Low-cost optical tracking of soccer players -- An Autoencoder Based Approach to SimulateSports Games -- Physical performance optimization in football -- Predicting Player Trajectoriesin Shot Situations in Soccer -- Stats Aren't Everything: Learning Strengths andWeaknesses of Cricket Players -- Prediction of tiers in the rankingof ice hockey players -- A Machine Learning Approach for Road CyclingRace Performance Prediction -- Mining Marathon Training Data to GenerateUseful User Proles -- Learning from partially labeled sequences forbehavioral signal annotation.
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