한국체육학회지자연과학편

Korean Alliance for Health: Physical Education: Recreation:and Dance (한국체육학회)
권호 표지

The cluster analysis using Self-Organized Map in sport science

자기구성지도(Self-Organized Map)를 활용한 군집분석

Choi, Hyong-Jun;Kim, Joo-Hak;Go, Byoung-Gu
최형준;김주학;고병구

  • Published : 2007.09.29
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Abstract

Within this study, the self-organised map (SOM) which has clustering algorithms and enabling to visualize the data process has introduced with the clustering of sports events based on morphological similarity. The Matlab by Mathworks Ltd. and SOM toolbox have used to design and determine the SOM in this study that the results have compared with the study by Go(2003). Overall, the number of clusters by the SOM has found as 7, but it has been detected to 5 for the comparison. Secondly, the unfamiliar results with Go's(2003) have found that the Biathlon, High jump, Skating, Triathlon, Weight lifting and Wresting have categorized into different clusters when the clustering conditions has been equalized. Thirdly, the Triathlon has not been in the same cluster group even other sports have contained in the same cluster groups when the alternative condition to cluster the data. Consequently, the potential application of Self-Organized Map technique has suggested through this study.

Keywords

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