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Self-Organizing Maps Combined with Eigenmode Analysis for Automated Cluster Identification (1999)

Galliat, Tobias ; Huisinga, Wilhelm ; Deuflhard, Peter

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Publication Date: 2014-02-26

Description: One of the important tasks in Data Mining is automated cluster analysis. Self-Organizing Maps (SOMs) introduced by {\sc Kohonen} are, in principle, a powerful tool for this task. Up to now, however, its cluster identification part is still open to personal bias. The present paper suggests a new approach towards automated cluster identification based on a combination of SOMs with an eigenmode analysis that has recently been developed by {\sc Deuflhard et al.} in the context of molecular conformational dynamics. Details of the algorithm are worked out. Numerical examples from Data Mining and Molecular Dynamics are included.

Keywords: ddc:000

Language: English

Type: reportzib , doc-type:preprint

Format: application/postscript

Format: application/pdf

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