Bayesian Biclustering on Discrete Data
Variable Selection Methods
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Author
Contributions
- Liu, Jun - Contributor
- Harrington, David P. - Contributor
- Dasgupta, Tirthankar - Contributor
Publication
2013 - , Massachusetts
Language
English
Word Count
0 words, Guess
Page Count
0 pages
Identifiers
- OCLC Control Number870922958
- Open LibraryOL56932668M
Description
"Biclustering is a technique for clustering rows and columns of a data matrix simultaneously. Over the past few years, we have seen its applications in biology-related fields, as well as in many data mining projects. As opposed to classical clustering methods, biclustering groups objects that are similar only on a subset of variables. Many biclustering algorithms on continuous data have emerged over the last decade. In this dissertation, we will focus on two Bayesian biclustering algorithms we developed for discrete data, more specifically categorical data and ordinal data."
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