%0 Journal Article
%A Kraskov, A.
%A Stoegbauer, H.
%A Andrzejak, R. G.
%A Grassberger, P.
%T Hierarchical clustering using mutual information
%J epl
%V 70
%@ 0295-5075
%C Les Ulis
%I EDP Sciences
%M PreJuSER-49823
%P 278 - 284
%D 2005
%Z Record converted from VDB: 12.11.2012
%X 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.
%K J (WoSType)
%F PUB:(DE-HGF)16
%9 Journal Article
%U <Go to ISI:>//WOS:000228627600020
%R 10.1209/epl/i2004-10483-y
%U https://juser.fz-juelich.de/record/49823