Package: tensorsparse 3.0

tensorsparse: Multiway Clustering via Tensor Block Models

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.

Authors:Miaoyan Wang, Yuchen Zeng

tensorsparse_3.0.tar.gz
tensorsparse_3.0.zip(r-4.7-x86_64)tensorsparse_3.0.zip(r-4.7-arm64)tensorsparse_3.0.zip(r-4.6-x86_64)tensorsparse_3.0.zip(r-4.6-arm64)tensorsparse_3.0.zip(r-4.5-x86_64)
tensorsparse_3.0.tgz(r-4.6-x86_64)tensorsparse_3.0.tgz(r-4.6-arm64)tensorsparse_3.0.tgz(r-4.5-x86_64)tensorsparse_3.0.tgz(r-4.5-arm64)
tensorsparse_3.0.tar.gz(r-4.7-arm64)tensorsparse_3.0.tar.gz(r-4.7-x86_64)tensorsparse_3.0.tar.gz(r-4.6-arm64)tensorsparse_3.0.tar.gz(r-4.6-x86_64)
tensorsparse_3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tensorsparse/json (API)

# Install 'tensorsparse' in R:
install.packages('tensorsparse', repos = c('https://yzeng58.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 2 scripts 240 downloads 5 exports 0 dependencies

Last updated from:34d0ad9eec. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK71
linux-devel-x86_64OK93
source / vignettesOK129
linux-release-arm64OK68
linux-release-x86_64OK83
macos-release-arm64OK89
macos-release-x86_64OK293
macos-oldrel-arm64OK81
macos-oldrel-x86_64OK304
windows-devel-arm64OK328
windows-devel-x86_64OK105
windows-release-arm64OK289
windows-release-x86_64OK52
windows-oldrel-x86_64OK71
wasm-releaseOK65

Exports:chooseClusteringSizechooseLambdagetOrder3TensorgetOrder4TensortbmClustering

Dependencies: