TCLUST: trimming approach of robust clustering method
TCLUST is a method in statistical clustering technique which is based on modification of trimmed k-means clustering algorithm. It is called “crisp” clustering approach because the observation is can be eliminated or assigned to a group. TCLUST strengthen the group assignment by putting constraint to...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/33569/1/RobiahAdnan2012_TCLUSTTrimmingApproachofRobustClusteringMethod.pdf http://eprints.utm.my/id/eprint/33569/ http://mjfas.ibnusina.utm.my/index.php/jfs/article/view/312 |
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| Summary: | TCLUST is a method in statistical clustering technique which is based on modification of trimmed k-means clustering algorithm. It is called “crisp” clustering approach because the observation is can be eliminated or assigned to a group. TCLUST strengthen the group assignment by putting constraint to the cluster scatter matrix. The emphasis in this paper is to restrict on the eigenvalues, λ of the scatter matrix. The idea of imposing constraints is to maximize the log-likelihood function of spurious-outlier model. A review of different robust clustering approach is presented as a comparison to TCLUST methods. This paper will discuss the nature of TCLUST algorithm and how to determine the number of cluster or group properly and measure the strength of group assignment. At the end of this paper, R-package on TCLUST implement the types of scatter restriction, making the algorithm to be more flexible for choosing the number of clusters and the trimming proportion. |
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