6 resultados para cluster analysis

em Bulgarian Digital Mathematics Library at IMI-BAS


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The paper treats the task for cluster analysis of a given assembly of objects on the basis of the information contained in the description table of these objects. Various methods of cluster analysis are briefly considered. Heuristic method and rules for classification of the given assembly of objects are presented for the cases when their division into classes and the number of classes is not known. The algorithm is checked by a test example and two program products (PP) – learning systems and software for company management. Analysis of the results is presented.

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In data mining, efforts have focused on finding methods for efficient and effective cluster analysis in large databases. Active themes of research focus on the scalability of clustering methods, the effectiveness of methods for clustering complex shapes and types of data, high-dimensional clustering techniques, and methods for clustering mixed numerical and categorical data in large databases. One of the most accuracy approach based on dynamic modeling of cluster similarity is called Chameleon. In this paper we present a modified hierarchical clustering algorithm that used the main idea of Chameleon and the effectiveness of suggested approach will be demonstrated by the experimental results.

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2000 Mathematics Subject Classification: 62H30, 62M10, 62M20, 62P20, 94A13.

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2000 Mathematics Subject Classification: 62H30

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2000 Mathematics Subject Classification: 62P10, 62H30

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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015