Build a Metric Subspaces Data Model for a Data Source R package ganDataModel version 2.0.1 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>. Software Imports: Rcpp (>= 1.0.3), tensorflow (>= 2.0.0) LinkingTo: Rcpp Werner Mueller <werner.mueller5@chello.at> Comprehensive R Archive Network (CRAN) Werner Mueller [aut, cre] GPL (>= 2) 2025-12-19 application/tgz https://CRAN.R-project.org/package=ganDataModel doi:10.32614/CRAN.package.ganDataModel