dorsal/arxiv
View SchemaHierarchical Clustering Using Mutual Information
| Authors | Alexander Kraskov, Harald Stoegbauer, Ralph G. Andrzejak, Peter Grassberger |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0311037 |
| URL | https://arxiv.org/abs/q-bio/0311037 |
Abstract
We present a method for hierarchical clustering of data called {\it 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.
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"abstract": "We present a method for hierarchical clustering of data called {\\it mutual\ninformation clustering} (MIC) algorithm. It uses mutual information (MI) as a\nsimilarity measure and exploits its grouping property: The MI between three\nobjects $X, Y,$ and $Z$ is equal to the sum of the MI between $X$ and $Y$, plus\nthe MI between $Z$ and the combined object $(XY)$. We use this both in the\nShannon (probabilistic) version of information theory and in the Kolmogorov\n(algorithmic) version. We apply our method to the construction of phylogenetic\ntrees from mitochondrial DNA sequences and to the output of independent\ncomponents analysis (ICA) as illustrated with the ECG of a pregnant woman.",
"arxiv_id": "q-bio/0311037",
"authors": [
"Alexander Kraskov",
"Harald Stoegbauer",
"Ralph G. Andrzejak",
"Peter Grassberger"
],
"categories": [
"q-bio.QM",
"cs.CC",
"physics.data-an"
],
"title": "Hierarchical Clustering Using Mutual Information",
"url": "https://arxiv.org/abs/q-bio/0311037"
},
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