Implements the largeVis algorithm (see Tang, et al. (2016) ) 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.

Documentation

Manual: largeVis.pdf
Vignettes:

Maintainer: Amos Elberg <amos.elberg at gmail.com>

Author(s): Amos B. Elberg

Install package and any missing dependencies by running this line in your R console:

install.packages("largeVis")

Depends R (>= 3.0.2), Rcpp, Matrix
Imports ggplot2(>=2.1.0)
Suggests ggforce, testthat, knitr, rmarkdown, png, dbscan
Enhances
Linking to Rcpp(>=0.12.4), RcppProgress(>=0.2.1), RcppArmadillo(>=0.7.200.2.0), testthat(>=1.0.2)
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Package largeVis
Materials
URL https://github.com/elbamos/largeVis
Task Views Cluster
Version 0.2
Published 2017-03-08
License GPL-3
BugReports https://github.com/elbamos/largeVis/issues
SystemRequirements C++11
NeedsCompilation yes
Citation
CRAN checks largeVis check results
Package source largeVis_0.2.tar.gz