Hierarchical Clustering Using Mutual Information

Details Hierarchical Clustering Using Mutual Information Hierarchical Clustering Using Mutual Information

2003-11-27

arxiv.org/abs/q-bio/0311037v1

Biology

Quantitative Biology

Quantitative Methods

4 pages, 4 figures

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

Hierarchical Clustering Using Mutual Information does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Hierarchical Clustering Using Mutual Information, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Hierarchical Clustering Using Mutual Information will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-519405