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http://hdl.handle.net/2122/6184
Authors: | Adelfio, Giada* Chiodi, Marcello* D'Alessandro, Antonino* Luzio, Dario* |
Title: | Functional Principal Components direction to cluster earthquake | Issue Date: | 2-May-2010 | Keywords: | Waveforms clustering | Subject Classification: | 04. Solid Earth::04.06. Seismology::04.06.99. General or miscellaneous | Abstract: | Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). In this paper we combine the aim of finding clusters from a set of individual curves to the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. We apply a classical clustering method to rotated data, according to the direction of maximum variance. A k-means clustering algorithm based on PCA rotation of data is proposed, as an alternative to methods that require previous interpolation of data based on splines or linear fitting (García-Escudero and Gordaliza (2005), Tarpey (2007), Sangalli et al. (2008)). |
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EGU2010-10344-1.pdf | EGU Abstract | 99.67 kB | Adobe PDF | View/Open |
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