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tensorsparse  

Multiway Clustering via Tensor Block Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("tensorsparse", "3.0")



Attach the package and use:
library("tensorsparse")
Maintained by
Yuchen Zeng
[Scholar Profile | Author Map]
First Published: 2019-08-05
Latest Update: 2020-09-27
Description:
Implements the multiway sparse clustering approach of M. Wang and Y. Zeng, "Multiway clustering via tensor block models". Advances in Neural Information Processing System 32 (NeurIPS), 715-725, 2019.
How to cite:
Yuchen Zeng (2019). tensorsparse: Multiway Clustering via Tensor Block Models. R package version 3.0, https://cran.r-project.org/web/packages/tensorsparse. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0 (2019-08-05 15:40), 2.0 (2020-03-22 08:10)
Other packages that cited tensorsparse R package
View tensorsparse citation profile
Other R packages that tensorsparse depends, imports, suggests or enhances
Complete documentation for tensorsparse
Functions, R codes and Examples using the tensorsparse R package
Some associated functions: chooseClusteringSize . chooseLambda . getOrder3Tensor . getOrder4Tensor . tbmClustering . 
Some associated R codes: chooseClusteringSize.R . chooseLambda.R . functions.R . getOrder3Tensor.R . getOrder4Tensor.R . tbmClustering.R .  Full tensorsparse package functions and examples
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