Package: ganDataModel 1.1.7

Werner Mueller

ganDataModel: Build a Metric Subspaces Data Model for a Data Source

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>.

Authors:Werner Mueller

ganDataModel_1.1.7.tar.gz
ganDataModel_1.1.7.tar.gz(r-4.5-noble)ganDataModel_1.1.7.tar.gz(r-4.4-noble)
ganDataModel.pdf |ganDataModel.html
ganDataModel/json (API)

# Install 'ganDataModel' in R:
install.packages('ganDataModel', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

12 exports 0.23 score 30 dependencies 2 scripts 424 downloads

Last updated 2 months agofrom:01d2e34823. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 21 2024
R-4.5-linux-x86_64OKAug 21 2024

Exports:dmBuildMetricSubspacesdmCalculateDensityValuedmGetContainedInMetricSubspacesdmGetLevelsdmGetMetricSubspacePropertiesdmPlotEvaluateDataSourceParametersdmPlotMetricSubspaceParametersdmPlotMetricSubspacesdmReaddmRemoveMetricSubspacesdmResetdmTrain

Dependencies:backportsbase64enccliconfigglueherejsonlitelatticelifecyclemagrittrMatrixpngprocessxpsR6rappdirsRcppRcppTOMLreticulaterlangrprojrootrstudioapitensorflowtfautographtfrunstidyselectvctrswhiskerwithryaml