Distance Metrics for Time-Series Data with Concentric Multi-Sphere Self Organizing Maps

Gedeon, Tamas (Tom); Paget, Lachlan; Zhu, Dingyun

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Distance Metrics for Time-Series Data with Concentric Multi-Sphere Self Organizing Maps

Date

2013

Authors

Gedeon, Tamas (Tom)

Paget, Lachlan

Zhu, Dingyun

Publisher

Springer

Abstract

Self-Organizing Maps have been shown to be a powerful unsupervised learning a tool in the analysis of complex high dimensional data. SOMs are capable of performing topological mapping, clustering and dimensionality reduction in order to effectively visual

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http://hdl.handle.net/1885/66432

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ANU Research Publications

Source

Lecture Notes in Computer Science (LNCS)

Type

Journal article

DOI

10.1007/978-3-642-42042-9_94

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2037-12-31

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01_Gedeon_Distance_Metrics_for_2013.pdf (570.81 KB)

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Distance Metrics for Time-Series Data with Concentric Multi-Sphere Self Organizing Maps

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