largeVis: High-Quality Visualizations of Large, High-Dimensional Datasets

Implements the largeVis algorithm (see Tang, et al. (2016) <https://arxiv.org/abs/1602.00370>) for visualizing very large high-dimensional datasets. Also very fast search for approximate nearest neighbors; outlier detection; and optimized implementations of the HDBSCAN*, DBSCAN and OPTICS clustering algorithms; plotting functions for visualizing the above.

Version: 0.1.10.2
Depends: R (≥ 3.0.2), Matrix
Imports: Rcpp (≥ 0.12.4), ggplot2 (≥ 0.9.2.1), dbscan
LinkingTo: Rcpp, RcppProgress (≥ 0.2.1), RcppArmadillo (≥ 0.7.200.2.0), testthat (≥ 1.0.2)
Suggests: testthat, covr, knitr, rmarkdown, wesanderson, RColorBrewer, dplyr, png, magrittr
Published: 2016-11-27
Author: Amos B. Elberg
Maintainer: Amos Elberg <amos.elberg at gmail.com>
BugReports: https://github.com/elbamos/largeVis/issues
License: GPL-3
URL: https://github.com/elbamos/largeVis
NeedsCompilation: yes
SystemRequirements: C++11
Materials: NEWS
In views: Cluster
CRAN checks: largeVis results

Downloads:

Reference manual: largeVis.pdf
Vignettes: largeVis
largeVisnewfeatures
Package source: largeVis_0.1.10.2.tar.gz
Windows binaries: r-devel: largeVis_0.1.10.2.zip, r-release: largeVis_0.1.10.2.zip, r-oldrel: not available
OS X Mavericks binaries: r-release: largeVis_0.1.10.2.tgz, r-oldrel: largeVis_0.1.10.2.tgz
Old sources: largeVis archive

Linking:

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