On Clustering Time Series Using Euclidean Distance and Pearson Correlation

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BERTHOLD, Michael R., Frank HÖPPNER, 2016. On Clustering Time Series Using Euclidean Distance and Pearson Correlation

@techreport{Berthold2016Clust-34784, title={On Clustering Time Series Using Euclidean Distance and Pearson Correlation}, year={2016}, author={Berthold, Michael R. and Höppner, Frank} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/34784"> <dc:contributor>Höppner, Frank</dc:contributor> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/34784"/> <dcterms:abstract xml:lang="eng">For time series comparisons, it has often been observed that z-score normalized Euclidean distances far outperform the unnormalized variant. In this paper we show that a z-score normalized, squared Euclidean Distance is, in fact, equal to a distance based on Pearson Correlation. This has profound impact on many distance-based classification or clustering methods. In addition to this theoretically sound result we also show that the often used k-Means algorithm formally needs a mod ification to keep the interpretation as Pearson correlation strictly valid. Experimental results demonstrate that in many cases the standard k-Means algorithm generally produces the same results.</dcterms:abstract> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-07-13T13:07:14Z</dcterms:available> <dc:creator>Höppner, Frank</dc:creator> <dc:contributor>Berthold, Michael R.</dc:contributor> <dcterms:issued>2016</dcterms:issued> <dc:creator>Berthold, Michael R.</dc:creator> <dcterms:rights rdf:resource="http://nbn-resolving.de/urn:nbn:de:bsz:352-20150914100631302-4485392-8"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-07-13T13:07:14Z</dc:date> <dcterms:title>On Clustering Time Series Using Euclidean Distance and Pearson Correlation</dcterms:title> <dc:language>eng</dc:language> </rdf:Description> </rdf:RDF>

Dateiabrufe seit 13.07.2016 (Informationen über die Zugriffsstatistik)

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