Density Based Clustering Scheme Using Dynamic Dissimilarity Measures

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Provided by: International Journal of Engineering and Advanced Technology (IJEAT)
Topic: Data Management
Format: PDF
Clustering methods are used support estimates of a data distribution have newly attracted much attention because of their ability to generate cluster boundaries of arbitrary shape and to contract with outliers efficiently. This paper proposes a density based clustering using dynamic dissimilarity measure based on a dynamical system associated with density estimating functions. Hypothetical basics of the proposed measure are developed and applied to construct a clustering method that can efficiently partition the whole data space.
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