Package: ganGenerativeData
Type: Package
Title: Generate Generative Data for a Data Source
Version: 2.1.4
Date: 2024-12-13
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: 7.2.3
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: 2024-12-12 12:11:17 UTC; r
Repository: CRAN
Date/Publication: 2024-12-12 13:20:01 UTC
Built: R 4.3.3; x86_64-apple-darwin20; 2024-12-12 14:36:40 UTC; unix
Archs: ganGenerativeData.so.dSYM
