Uniform manifold approximation and projection is a technique for dimension reduction. The algorithm was described by McInnes and Healy (2018) in <doi:10.48550/arXiv.1802.03426>. This package provides an interface for two implementations. One is written from scratch, including components for nearest-neighbor search and for embedding. The second implementation is a wrapper for 'python' package 'umap-learn' (requires separate installation, see vignette for more details).
| Version: | 0.2.10.0 |
| Depends: | R (≥ 3.6.0) |
| Imports: | Matrix, methods, openssl, reticulate, Rcpp (≥ 0.12.6), RSpectra, stats |
| LinkingTo: | Rcpp |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2023-02-01 |
| DOI: | 10.32614/CRAN.package.umap |
| Author: | Tomasz Konopka [aut, cre] |
| Maintainer: | Tomasz Konopka <tokonopka at gmail.com> |
| BugReports: | https://github.com/tkonopka/umap/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/tkonopka/umap |
| NeedsCompilation: | yes |
| CRAN checks: | umap results |
| Reference manual: | umap.pdf |
| Vignettes: |
Uniform Manifold Approximation and Projection in R Interfacing with 'umap-learn' |
| Package source: | umap_0.2.10.0.tar.gz |
| Windows binaries: | r-devel: umap_0.2.10.0.zip, r-release: umap_0.2.10.0.zip, r-oldrel: umap_0.2.10.0.zip |
| macOS binaries: | r-release (arm64): umap_0.2.10.0.tgz, r-oldrel (arm64): umap_0.2.10.0.tgz, r-release (x86_64): umap_0.2.10.0.tgz, r-oldrel (x86_64): umap_0.2.10.0.tgz |
| Old sources: | umap archive |
| Reverse depends: | KODAMA |
| Reverse imports: | animalcules, CelliD, chameleon, ChromSCape, COTAN, EmbedSOM, FateID, GEOexplorer, ggpca, HIPPO, HVT, ILoReg, InterCellar, jrSiCKLSNMF, karyotapR, M3C, MatrixQCvis, Mercator, musclesyneRgies, nevada, PhyloProfile, PIUMA, projectR, RaceID, RCSL, regioneReloaded, rrvgo, RSDA, SaturnCoefficient, scDataviz, scDesign3, sRACIPE, SuperCell, theftdlc, tomoda |
| Reverse suggests: | cola, crosshap, dimRed, HDCytoData, NGCHM, OlinkAnalyze, OTclust, pctax, Platypus, ProjectionBasedClustering, qeML, quollr, scPipe, seriation, SPIAT, UCSCXenaShiny |
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