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 <johntreisner@gmail.com>
LicenseMIT + file LICENSE
Version0.2.3
URL https://github.com/jreisner/biclustermd
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("biclustermd")

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biclustermd documentation built on June 17, 2021, 5:11 p.m.