Journal Article

PreJuSER-49823

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Hierarchical clustering using mutual information

Kraskov, A.FZJ* ; Stoegbauer, H.FZJ* ; Andrzejak, R. G.FZJ* ; Grassberger, P.FZJ*

2005
EDP Sciences Les Ulis

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Please use a persistent id in citations: http://hdl.handle.net/2128/22927  doi:10.1209/epl/i2004-10483-y

Abstract: We present a conceptually simple method for hierarchical clustering of data called mutual information clustering ( MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects X, Y, and Z is equal to the sum of the MI between X and Y, plus the MI between Z and the combined object (XY). We use this both in the Shannon (probabilistic) version of information theory and in the Kolmogorov ( algorithmic) version. We apply our method to the construction of phylogenetic trees from mitochondrial DNA sequences and to the output of independent components analysis (ICA) as illustrated with the ECG of a pregnant woman.

Keyword(s): J

Note: Record converted from VDB: 12.11.2012

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Contributing Institute(s):

1. John von Neumann - Institut für Computing (NIC)

Research Program(s):

1. Betrieb und Weiterentwicklung des Höchstleistungsrechners (I03)

Appears in the scientific report 2005

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Database coverage:
; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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