PG-means: Learning the number of clusters in data

Advances in Neural Information Processing Systems

Volumn , Issue , 2007, Pages 393-400

  Feng, Yu ^a   Hamerly, Greg ^a  

^a Baylor University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN MIXTURE MODEL; HIGH DIMENSIONS; NON-GAUSSIAN DATA; NOVEL ALGORITHM; NUMBER OF CLUSTERS; OVERLAPPING CLUSTERS; STATISTICAL HYPOTHESIS TEST;

ALGORITHMS;

STATISTICAL TESTS;

EID: 58549087543     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Hirotugu Akaike. A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19:716-723, 1974.
2. Gerard E. Dallal and Leland Wilkinson. An analytic approximation to the distribution of Lilliefors' test for normality. The American Statistician, 40:294-296, 1986.
3. Sanjoy Dasgupta. Experiments with random projection. In Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI-2000), pages 143-151. Morgan Kaufmann Publishers, 2000.
4. Greg Hamerly and Charles Elkan. Learning the k in k-means. In Proceedings of the seventeenth annual conference on neural information processing systems (NIPS), pages 281-288, 2003.
5. Robert E. Kass and LarryWasserman. A reference Bayesian test for nested hypotheses and its relationship to the schwarz criterion. Journal of the American Statistical Association, 90(431):928-934, 1995.
6. Hubert W. Lilliefors. On the Kolmogorov-Smirnov test of normality with mean and variance unknown. Journal of the American Statistical Association, 62(318):399-402, 1967.
7. Frank J.Massey, Jr. The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association, 46(253):68-78, 1951.
8. Marina Meila. Comparing clusterings by the variation of information. In COLT, pages 173-187, 2003.
9. Dan Pelleg and Andrew Moore. X-means: Extending k-means with efficient estimation of the number of clusters. In Proceedings of the 17th International Conf. on Machine Learning, pages 727-734. Morgan Kaufmann, 2000.
10. Jorma Rissanen. Modeling by shortest data description. Automatica, 14:465-471, 1978.
11. Peter Sand and Andrew W. Moore. Repairing faulty mixture models using density estimation. In Proceedings of the 18th International Conf. on Machine Learning, pages 457-464, 2001.
12. Gideon Schwarz. Estimating the dimension of a model. The Annnals of Statistics, 6(2):461-464, 1978.
13. Robert Tibshirani, Guenther Walther, and Trevor Hastie. Estimating the number of clusters in a dataset via the Gap statistic. Journal of the Royal Statistical Society B, 63:411-423, 2001.
14. Naonori Ueda and Ryohei Nakano. Deterministic annealing em algorithm. Neural Networks, 11(2):271-282, 1998.
15. Max Welling and Kenichi Kurihara. Bayesian k-means as a 'maximization-expectation' algorithm. In SIAM conference on Data Mining SDM06, 2006.