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Unsupervised clustering protocol for large scale structured data, based on a low dimensional representation of the data. Dimensionality reduction is performed using a parallelized implementation of the t-Stochastic Neighboring Embedding algorithm (Garriga J. and Bartumeus F. (2018), <doi:10.48550/arXiv.1812.09869>).
| Version: | 2.3.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp (≥ 0.12.0), bigmemory (≥ 4.5.0), parallel (≥ 3.5.0), RColorBrewer, colorspace |
| LinkingTo: | Rcpp, RcppArmadillo, BH, bigmemory |
| Suggests: | knitr, rmarkdown |
| Published: | 2020-06-30 |
| Author: | Joan Garriga [aut, cre], Frederic Bartumeus [aut] |
| Maintainer: | Joan Garriga <jgarriga at ceab.csic.es> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Materials: | NEWS |
| CRAN checks: | bigMap results |
| Reference manual: | bigMap.pdf |
| Vignettes: |
The bigMap R-package: quick reference |
| Package source: | bigMap_2.3.1.tar.gz |
| Windows binaries: | r-devel: bigMap_2.3.1.zip, r-release: bigMap_2.3.1.zip, r-oldrel: bigMap_2.3.1.zip |
| macOS binaries: | r-release (arm64): bigMap_2.3.1.tgz, r-oldrel (arm64): bigMap_2.3.1.tgz, r-release (x86_64): bigMap_2.3.1.tgz, r-oldrel (x86_64): bigMap_2.3.1.tgz |
| Old sources: | bigMap archive |
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