@inproceedings{58480c104f664c92a52161d864b73647,
title = "Robust clustering algorithms based on finite mixtures of multivariate t distribution",
abstract = "Providing protection against outlier in clustering data is a difficult problem. We proposed two robust clustering algorithms which integrate two modified versions of EM algorithm for mixtures t model with a model selection criterion respectively. The proposed methods can select the number of clusters component automatically by a combined component annihilation strategy and can also avoid the drawbacks of traditional mixture-based clustering algorithms - highly dependent on initialization and may converge to the boundary of the parameter space [7]. Experiment results show the contrast among different algorithms and demonstrate the effectiveness of our algorithms.",
author = "Chengwen Yu and Zhang Qianjin and Lei Guo",
year = "2006",
doi = "10.1007/11881070_83",
language = "英语",
isbn = "3540459014",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "606--609",
booktitle = "Advances in Natural Computation - Second International Conference, ICNC 2006, Proceedings,",
note = "2nd International Conference on Natural Computation, ICNC 2006 ; Conference date: 24-09-2006 Through 28-09-2006",
}