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.
- Version0.2.3
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release06/17/2021
Documentation
Team
John Reisner
Jing Li
Show author detailsRolesContributor, Copyright holderHieu Pham
Show author detailsRolesContributor, Copyright holder
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- Depends2 packages
- Imports7 packages
- Suggests3 packages