Abstract
In data clustering, many approaches have been proposed such as K-means method and hierarchical method. One of the problems is that the results depend heavily on initial values and criterion to combine clusters.
In this investigation, we propose a new method to avoid this deficiency. Here we assume there exists aspects of local regression in data. Then we develop our theory to combine clusters using \(\mathcal{F}\) values by regression analysis as criterion. We examine experiments and show how well the theory works.
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© 2003 Springer-Verlag Berlin Heidelberg
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Motoyoshi, M., Miura, T., Shioya, I. (2003). Clustering by Regression Analysis. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2003. Lecture Notes in Computer Science, vol 2737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45228-7_21
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DOI: https://doi.org/10.1007/978-3-540-45228-7_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40807-9
Online ISBN: 978-3-540-45228-7
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