منابع مشابه
Macrostate data clustering.
We develop an effective nonhierarchical data clustering method using an analogy to the dynamic coarse graining of a stochastic system. Analyzing the eigensystem of an interitem transition matrix identifies fuzzy clusters corresponding to the metastable macroscopic states (macrostates) of a diffusive system. A "minimum uncertainty criterion" determines the linear transformation from eigenvectors...
متن کاملPractical Uncertainty Minimization for Spectral Macrostate Data Clustering
Spectral clustering, which uses the global information embedded in eigenvectors of an inter-item relation matrix, can outperform traditional approaches such as k-means and hierarchical clustering. Spectral hierarchical bipartitioning is well-understood, but spectral multipartitioning remains an interesting research topic. Korenblum and Shalloway [Phys. Rev. E 67, 056704 (2003)] used an analogy ...
متن کاملEfficient uncertainty minimization for spectral macrostate data clustering
Spectral clustering, which uses the global information embedded in eigenvectors of an interitem relationship matrix, can outperform traditional approaches such as k-means and hierarchical clustering. Spectral hierarchical bipartitioning is well-understood, but spectral multipartitioning remains an interesting research topic. Korenblum and Shalloway [Phys. Rev. E 67, 056704 (2003)] used an analo...
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The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...
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The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal fuzzy data. Then, as an application, a method based on the proposed algorithm is pres...
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ژورنال
عنوان ژورنال: Physical Review E
سال: 2003
ISSN: 1063-651X,1095-3787
DOI: 10.1103/physreve.67.056704