Package: ganGenerativeData
Type: Package
Title: Generate Generative Data for a Data Source
Version: 2.1.6
Date: 2025-12-16
Author: Werner Mueller [aut, cre]
Maintainer: Werner Mueller <werner.mueller5@chello.at>
Description: Generative Adversarial Networks are applied to generate
        generative data for a data source. A generative model
        consisting of a generator and a discriminator network is
        trained. During iterative training the distribution of
        generated data is converging to that of the data source. Direct
        applications of generative data are the created functions for
        data evaluation, missing data completion and data
        classification. A software service for accelerated training of
        generative models on graphics processing units is available.
        Reference: Goodfellow et al. (2014)
        <doi:10.48550/arXiv.1406.2661>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.3), tensorflow (>= 2.0.0), httr (>= 1.4.7)
LinkingTo: Rcpp
RoxygenNote: 7.3.3
SystemRequirements: TensorFlow (https://www.tensorflow.org)
NeedsCompilation: yes
Encoding: UTF-8
Authors@R: person(given = "Werner", family = "Mueller", role = c("aut", "cre"), email = "werner.mueller5@chello.at")
Packaged: 2026-10-10 14:58:28 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2025-12-16 22:20:02 UTC
RemoteUrl: https://github.com/cran/ganGenerativeData
RemoteRef: HEAD
RemoteSha: a93bf5f352cb1d637e5e12eb2dea5b6a99ebcb47
Built: R 4.7.0; aarch64-unknown-linux-gnu; 2026-10-10 15:00:16 UTC; unix
