k-ATTRACTORS: A PARTITIONAL CLUSTERING ALGORITHM FOR NUMERIC DATA ANALYSIS

Clustering is a data analysis technique, particularly useful when there are many dimensions and little prior information about the data. Partitional clustering algorithms are efficient but suffer from sensitivity to the initial partition and noise. We propose here k-attractors, a partitional cluster...

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Bibliographic Details

Published in:	Applied artificial intelligence Vol. 25; no. 2; pp. 97 - 115
Main Authors:	Kanellopoulos, Y., Antonellis, P., Tjortjis, C., Makris, C., Tsirakis, N.
Format:	Journal Article
Language:	English
Published:	Philadelphia Taylor & Francis Group 28.02.2011 Taylor & Francis Ltd
Subjects:	Acceptability Accuracy Algorithms Artificial intelligence Cluster analysis Clustering Clusters Convergence Data analysis Data processing Expert systems Mathematical models Numerical analysis Preprocessing
ISSN:	0883-9514, 1087-6545
Online Access:	Get full text
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