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biclustermd  

Biclustering with Missing Data
View on CRAN: Click here


Download and install biclustermd package within the R console
Install from CRAN:
install.packages("biclustermd")

Install from Github:
library("remotes")
install_github("cran/biclustermd")

Install by package version:
library("remotes")
install_version("biclustermd", "0.2.3")



Attach the package and use:
library("biclustermd")
Maintained by
John Reisner
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-09-30
Latest Update: 2021-06-17
Description:
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
How to cite:
John Reisner (2019). biclustermd: Biclustering with Missing Data. R package version 0.2.3, https://cran.r-project.org/web/packages/biclustermd. Accessed 06 Jan. 2025.
Previous versions and publish date:
0.1.0 (2019-09-30 13:40), 0.2.0 (2019-12-07 06:20), 0.2.1 (2020-02-18 06:30), 0.2.2 (2020-04-15 07:10)
Other packages that cited biclustermd R package
View biclustermd citation profile
Other R packages that biclustermd depends, imports, suggests or enhances
Complete documentation for biclustermd
Functions, R codes and Examples using the biclustermd R package
Some associated functions: as.Biclust . autoplot.biclustermd . autoplot.biclustermd_sim . autoplot.biclustermd_sse . biclustermd-package . biclustermd . binary_vector_gen . cell_heatmap . cell_mse . cluster_iteration_sum_sse . col.names.biclustermd . col.names . col_cluster_names . compare_biclusters . fill_empties_P . fill_empties_Q . format_partition . gather.biclustermd . jaccard_similarity . mse_heatmap . part_matrix_to_vector . partition_gen . partition_gen_by_p . position_finder . print.biclustermd . reorder_biclust . rep_biclustermd . results_heatmap . row.names.biclustermd . row_cluster_names . runtimes . synthetic . tune_biclustermd . 
Some associated R codes: as.Biclust.R . autoplot.biclustermd.R . autoplot.biclustermd_sim.R . autoplot.biclustermd_sse.R . biclustermd-package.R . biclustermd.R . binary_vector_gen.R . cell_heatmap.R . cell_mse.R . cluster_iteration_sum_sse.R . col.names.R . col.names.biclustermd.R . col_cluster_names.R . compare_biclusters.R . fill_empties_P.R . fill_empties_Q.R . format_partition.R . gather.biclustermd.R . globalvars.R . jaccard.R . mse_heatmap.R . part_matrix_to_vector.R . partition_gen.R . partition_gen_by_p.R . position_finder.R . print.R . reorder_biclust.R . rep_biclustermd.R . results_heatmap.R . row.names.biclustermd.R . row_cluster_names.R . runtimes.R . synthetic.R . tune_biclustermd.R .  Full biclustermd package functions and examples
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