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KDD
2002
ACM

SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets

14 years 4 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscillator and uses the relative similarity between the points to model the interaction between the oscillators. SyMP is robust to noise and outliers,determines the number of clusters in an unsupervised manner, identifies clusters of arbitrary shapes, and can handle very large data sets. The robusthesS of SyMP isan intrinsicproperty of the synchronization mechanism. To determine the optimum number of clusters, SyMP uses a dynamic resolution parameter. To identify clusters of various shapes, SyMP models each cluster by multiple Gaussian components. The number of components is automatically determined using a dynamic intra-cluster resolution parameter. Clusters with simple shapes would be modeled by few components while clusters with more complex shapes would require a larger number of components. The scalable versio...
Hichem Frigui
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2002
Where KDD
Authors Hichem Frigui
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