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ganDataModel

2.0.1Package record

Build a Metric Subspaces Data Model for a Data Source

0packages depend
3Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

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.

Install

Health

CRAN checks
13OK
Slowest check: 3.8 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK12 OK2026-04-25
  • NOTE13 OK, 1 NOTE2026-04-22
  • ERROR12 OK, 1 NOTE, 1 ERROR2026-04-18
Show 1 earlier changeHide 1 earlier change
  • NOTE13 OK, 1 NOTE2026-03-10
Advisories

none known

Documentation

In release 2.0.1
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
13includes a package overview page
Examples that run
0%13 never run
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
8%

Downloads

3K
CRAN downloads in the past year
Rank #16,343 · ~8/day · ~251/mo
Daily download trend is not available in this view yet.
26930 days
77190 days
3K1 year
Compare downloads with other packages →
Also on432 r2u3 autocran

Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)

Installing ganDataModel adds 28 packages (17 with compiled code, 11 MB of source tarballs). Heaviest: tfruns 1.9 MB, Rcpp 1.8 MB, reticulate 1.6 MB.

Depends (0)
none
Imports (2)
LinkingTo (1)
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (1)
Author, Maintainer since 1.0.2 (2022)
Releases (9)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 2.0.1Latest
    record
    2025-12-19 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 1.1.7
    record
    2024-07-21 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • 1.1.6
    record
    2024-01-21 · diff ↗
  • 1.1.5
    record
    2023-12-14 · diff ↗
  • 1.1.4
    record
    2023-05-07 · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • 1.1.3
    record
    2023-04-02 · diff ↗
  • 1.1.2
    record
    2023-03-05 · diff ↗
  • 1.1.1
    record
    2022-12-19 · diff ↗ ·
    removed 8 exports
    dmBuildSubspaces, dmRemoveSubspaces, dmGetAssignedSubspaces, dmPlotSubspaces, dmPlotGenerativeDataParameters, dmPlotSubspaceParameters, dmPlotEvaluate, dmGetNumberOfSubspaces
    added 6 exports
    dmBuildMetricSubspaces, dmRemoveMetricSubspaces, dmGetContainedInMetricSubspaces, dmPlotMetricSubspaces, dmPlotMetricSubspaceParameters, dmGetMetricSubspaceProperties
  • 1.0.2
    record
    2022-07-16
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2022-07-16
Total releases
9 / 4 yrs
License
GPL (>= 2) OSI
Download size
503 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ganDataModel")
Mueller, W. (2025). ganDataModel: Build a Metric Subspaces Data Model for a Data Source (Version 2.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.ganDataModel

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ganDataModel version 2.0.1 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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