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 Post subject: Initializing K-means Batch Clustering: A Critical Evaluation of
PostPosted: Mon Mar 26, 2012 11:14 am 
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Initializing K-means Batch Clustering: A Critical Evaluation of Several Techniques
Douglas Steinley and Michael J. Brusco

Abstract: K-means clustering is arguably the most popular technique for partitioning data. Unfortunately, K-means suffers from the well-known problem of locally optimal solutions. Furthermore, the final partition is dependent upon the initial configuration, making the choice of starting partitions all the more important. This paper evaluates 12 procedures proposed in the literature and provides recommendations for best practices.

Download : http://www.springerlink.com/content/d03770l01k0043m1/fulltext.pdf


(I hope its ok to post this paper although its not directly related to poker, but as K-means clustering is often the first step in opponent modeling its not to far away from a direct application)


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 Post subject: Re: Initializing K-means Batch Clustering: A Critical Evaluation of
PostPosted: Mon Mar 26, 2012 11:26 am 
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Moved to junk, not because it is junk, but because its not about poker. If this were accepted in poker papers, we would have to allow 10,000 other such papers.


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