Successive Binary Partition K-means Method for Clustering with Less Cluster Size Bias
Author:
Affiliation:
1. Tohoku University,Graduate School of Engineering,Sendai,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9886003/9885802/09886452.pdf?arnumber=9886452
Reference19 articles.
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2. k-means++: The advantages of careful seeding;vassilvitskii;Proceedings of the Eighth Annual ACM- SIAM Symposium on Discrete Algorithms,2006
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4. A comparison of document clustering techniques;steinbach;In Proc World Text Mining Conference,2000
5. Empirical evaluation of K-Means, Bisecting K-Means, Fuzzy C-Means and Genetic K-Means clustering algorithms
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