Package: node2vec 0.1.0

node2vec: Algorithmic Framework for Representational Learning on Graphs

Given any graph, the 'node2vec' algorithm can learn continuous feature representations for the nodes, which can then be used for various downstream machine learning tasks.The techniques are detailed in the paper "node2vec: Scalable Feature Learning for Networks" by Aditya Grover, Jure Leskovec(2016),available at <arxiv:1607.00653>.

Authors:Yang Tian [aut, cre], Xu Li [aut], Jing Ren [aut]

node2vec_0.1.0.tar.gz
node2vec_0.1.0.zip(r-4.7-any)node2vec_0.1.0.zip(r-4.6-any)node2vec_0.1.0.zip(r-4.5-any)
node2vec_0.1.0.tgz(r-4.6-any)node2vec_0.1.0.tgz(r-4.5-any)
node2vec_0.1.0.tar.gz(r-4.7-any)node2vec_0.1.0.tar.gz(r-4.6-any)
node2vec_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
node2vec/json (API)

# Install 'node2vec' in R:
install.packages('node2vec', repos = c('https://tianyang-0523.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • gene_edges - 6 edges information between two genes of human

On CRAN:

Conda:

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

2.00 score 8 scripts 223 downloads 104 mentions 1 exports 33 dependencies

Last updated from:a3586cb1fd. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK152
source / vignettesOK211
linux-releaseOK140
macos-releaseOK148
macos-oldrelOK207
windows-develOK80
windows-releaseOK82
windows-oldrelOK81
wasm-releaseOK115

Exports:node2vecR

Dependencies:cliclustercpp11data.tabledplyrgenericsglueigraphjsonlitelatticelifecyclemagrittrMASSMatrixmgcvnlmepermutepillarpkgconfigR6RcppRcppProgressrlangrlisttibbletidyselectutf8vctrsveganwithrword2vecXMLyaml