An implementation of the Uniform Manifold Approximation and
Projection dimensionality reduction by McInnes et al. (2018)
<doi:10.48550/arXiv.1802.03426>. It also provides means to transform new data and
to carry out supervised dimensionality reduction. An implementation of
the related LargeVis method of Tang et al. (2016) <doi:10.48550/arXiv.1602.00370>
is also provided. This is a complete re-implementation in R (and C++,
via the 'Rcpp' package): no Python installation is required. See the
uwot website (<https://github.com/jlmelville/uwot>) for more
documentation and examples.
Version: |
0.2.2 |
Depends: |
Matrix |
Imports: |
FNN, irlba, methods, Rcpp, RcppAnnoy (≥ 0.0.17), RSpectra |
LinkingTo: |
dqrng, Rcpp, RcppAnnoy, RcppProgress |
Suggests: |
bigstatsr, covr, knitr, RcppHNSW, rmarkdown, rnndescent, testthat |
Published: |
2024-04-21 |
DOI: |
10.32614/CRAN.package.uwot |
Author: |
James Melville [aut, cre, cph],
Aaron Lun [ctb],
Mohamed Nadhir Djekidel [ctb],
Yuhan Hao [ctb],
Dirk Eddelbuettel [ctb] |
Maintainer: |
James Melville <jlmelville at gmail.com> |
BugReports: |
https://github.com/jlmelville/uwot/issues |
License: |
GPL (≥ 3) |
URL: |
https://github.com/jlmelville/uwot,
https://jlmelville.github.io/uwot/ |
NeedsCompilation: |
yes |
Materials: |
NEWS |
CRAN checks: |
uwot results |