biclustermd: Biclustering with Missing Data

Biclustering is a statistical learning technique that simultaneously partitions and clusters rows and columns of a data matrix. Since the solution space of biclustering is in infeasible to completely search with current computational mechanisms, this package uses a greedy heuristic. The algorithm featured in this package is, to the best our knowledge, the first biclustering algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H., Olafsson, S., and Vardeman, S. (2020) Biclustering with Missing Data. Information Sciences, 510, 304–316.

Package details

AuthorJohn Reisner [cre, aut, cph], Hieu Pham [ctb, cph], Jing Li [ctb, cph]
MaintainerJohn Reisner <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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biclustermd documentation built on June 17, 2021, 5:11 p.m.