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http://dx.doi.org/10.7583/JKGS.2013.13.4.15

Comparison of LDA and PCA for Korean Pro Go Player's Opening Recognition  

Lee, Byung-Doo (Dept. of Baduk Studies, Division of Sports Science, Sehan University)
Publication Information
Journal of Korea Game Society / v.13, no.4, 2013 , pp. 15-24 More about this Journal
Abstract
The game of Go, which is originated at least more than 2,500 years ago, is one of the oldest board games in the world. So far the theoretical studies concerning to the Go openings are still insufficient. We applied traditional LDA algorithm to recognize a pro player's opening to a class obtained from the training openings. Both class-independent LDA and class-dependent LDA methods are conducted with the Go game records of the Korean top 10 professional Go players. Experimental result shows that the average recognition rate of class-independent LDA is 14% and class-dependent LDA 12%, respectively. Our research result also shows that in contrary to our common sense the algorithm based on PCA outperforms the algorithm based on LDA and reveals the new fact that the Euclidean distance metric method rarely does not inferior to LDA.
Keywords
Go openings; Linear Discriminant Analysis; Principal Component Analysis; Euclidean distance metric;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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