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Many optimization based clustering algorithms suffer from the possibility of stopping at locally optimal partitions of data sets. In this paper, we present a genetic. A new subspace clustering algorithm, PARTCAT, is proposed to cluster high dimensional categorical data. The architecture of PARTCAT is based on the. [1] Z. Huang, “Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values Data Mining and Knowledge. Toggle navigation. Data clustering : algorithms and applications Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Full description Saved in:. Minería de datos. Aggarwal, Chandan K. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. AAAI Press. Prof. Brendan Murphy - Model-based clustering for multivariate categorical dataACM Press. Lecture Notes in Computer Science : LNCS Vol. Springer Verlag. Web-scale k-means clustering. Data Mining and Knowledge Discovery 2 : Ng and J. Int'l Conf. ![]() Data Mining and Knowledge Discovery 11 : 5. In: Proc. SIAM Int. Learning Theory and Kernel Machines. Hierarchical Clustering Based on Mutual Information. July 18—23, Science : Introduction to Information Retrieval. Cambridge University Press. Journal of Cybernetics 4 : En Fern, Xiaoli Z. Hubert et P. ![]() Comparing partitions. Journal of the American Statistical Association, 78 — Categorías : Minería de datos Geoestadística. Espacios de nombres Artículo Discusión. Qing, H. Gao, X. Huang, Z. Sigue a los autoresIEEE Trans. Kononenko, I. Springer, Heidelberg Google Scholar. Li, J. Everitt, B. Heinemann Educational Books, New York, pp.
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