Information-based clustering

Information-based clustering.

In an age of increasingly large data sets, investigators in many different disciplines have turned to clustering as a tool for data analysis and exploration. Existing clustering methods, however, typically depend on several nontrivial assumptions about the structure of data. Here, we reformulate the clustering problem from an information theoretic perspective that avoids many of these assumptio...

Clustering Based on Kolmogorov Information

Résumé In this paper we show how to reduce the computational cost of Clustering by Compression, proposed by Cilibrasi & Vitànyi, from O(n) to O(n). To that end, we adopte the Weighted Paired Group Method using Averages (WPGMA) method to the same similarity measure, based on compression, used in Clustering by Compression. Consequently, our proposed approach has easily classified thousands of dat...

Information based clustering: Supplementary material

This technical report provides the supplementary material for a paper entitled " Information based clustering, " to appear shortly in Proceedings of the National Academy of Sciences (USA). In Section I we present in detail the iterative clustering algorithm used in our experiments and in Section II we describe the validation scheme used to determine the statistical significance of our results. ...

Gene Clustering Based on Clusterwide Mutual Information

Cluster analysis of gene-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and constructing gene regulatory networks. The motivation for considering mutual information is its capacity to measure a general dependence among gene random variables. We propose a novel clustering strategy based on min...

Fast Agglomerative Information Bottleneck Based Trajectory Clustering