ganGenerativeData: Generate Generative Data for a Data Source

Generative Adversarial Networks are applied to generate generative data for a data source. In iterative training steps the distribution of generated data converges to that of the data source. Reference: Goodfellow et al. (2014) <arXiv:1406.2661v1>.

Version: 1.1.1
Imports: Rcpp (≥ 1.0.3), tensorflow (≥ 2.0.0)
LinkingTo: Rcpp
Published: 2021-05-24
Author: Werner Mueller
Maintainer: Werner Mueller <werner.mueller5 at chello.at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: ganGenerativeData results

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Reference manual: ganGenerativeData.pdf
Package source: ganGenerativeData_1.1.1.tar.gz
Windows binaries: r-devel: ganGenerativeData_1.1.1.zip, r-devel-UCRT: ganGenerativeData_1.1.1.zip, r-release: ganGenerativeData_1.1.1.zip, r-oldrel: ganGenerativeData_1.1.1.zip
macOS binaries: r-release (arm64): ganGenerativeData_1.1.1.tgz, r-release (x86_64): ganGenerativeData_1.1.1.tgz, r-oldrel: ganGenerativeData_1.1.1.tgz
Old sources: ganGenerativeData archive

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