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tensorregress  

Supervised Tensor Decomposition with Side Information
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("tensorregress", "5.1")



Attach the package and use:
library("tensorregress")
Maintained by
Jiaxin Hu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-11-04
Latest Update: 2023-06-20
Description:
Implement the alternating algorithm for supervised tensor decomposition with interactive side information. Details can be found in the publication Hu, Jiaxin, Chanwoo Lee, and Miaoyan Wang. "Generalized Tensor Decomposition with features on multiple modes." Journal of Computational and Graphical Statistics, Vol. 31, No. 1, 204-218, 2022 <doi:10.1080/10618600.2021.1978471>.
How to cite:
Jiaxin Hu (2019). tensorregress: Supervised Tensor Decomposition with Side Information. R package version 5.1, https://cran.r-project.org/web/packages/tensorregress. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0 (2019-11-04 17:30), 1.1 (2020-02-13 16:50), 2.0 (2020-03-17 21:30), 3.0 (2020-09-16 08:40), 4.0 (2021-06-21 06:40), 5.0 (2023-04-12 12:10)
Other packages that cited tensorregress R package
View tensorregress citation profile
Other R packages that tensorregress depends, imports, suggests or enhances
Complete documentation for tensorregress
Functions, R codes and Examples using the tensorregress R package
Some associated functions: HCP . Tensor-class . as.tensor . dim-methods . fold . hosvd . kronecker_list . nations . rand_tensor . sele_rank . sim_data . tensor_regress . ttl . ttm . tucker . unfold-methods . 
Some associated R codes: HCP.R . bricks.R . miscellanea.R . nations.R . speedglm.R . speedlm.R . tensor_class.R . tensor_decomp.R . tensor_product.R . tensor_regress.R . uncommented.R .  Full tensorregress package functions and examples
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Maintainer: Qi Qin (view profile)

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