Package: ganDataModel
Type: Package
Title: Build a Metric Subspaces Data Model for a Data Source
Version: 2.0.1
Date: 2025-12-19
Author: Werner Mueller [aut, cre]
Maintainer: Werner Mueller <werner.mueller5@chello.at>
Description: Neural networks are applied to create a density value function which approximates density values for a data source. The trained neural network is analyzed for different levels. For each level metric subspaces with density values above a level are determined. The obtained set of metric subspaces and the trained neural network are assembled into a data model. A prerequisite is the definition of a data source, the generation of generative data and the calculation of density values. These tasks are executed using package 'ganGenerativeData' <https://cran.r-project.org/package=ganGenerativeData>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.3), tensorflow (>= 2.0.0)
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: 2025-12-19 11:28:54 UTC; ubuntu
Repository: CRAN
Date/Publication: 2025-12-19 11:40:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-28 17:44:55 UTC; unix
Archs: ganDataModel.so.dSYM
