umap: Uniform Manifold Approximation and Projection
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).
Documentation:
Downloads:
Reverse dependencies:
| Reverse depends: |
KODAMA |
| Reverse imports: |
AbSolution, chameleon, EmbedSOM, emcAdr, FateID, ggpca, ggsem, HVT, jrSiCKLSNMF, karyotapR, mectx, Mercator, musclesyneRgies, nevada, polarisR, RaceID, RSDA, SaturnCoefficient, STATassist, SuperCell, tall, theftdlc |
| Reverse suggests: |
crosshap, dimRed, factoextra, finlabR, MiscMetabar, NGCHM, OlinkAnalyze, OTclust, pctax, ProjectionBasedClustering, qeML, seriation, TextAnalysisR, tmfast, topolow, UCSCXenaShiny |
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