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ganDataModel  

Build a Metric Subspaces Data Model for a Data Source
View on CRAN: Click here


Download and install ganDataModel package within the R console
Install from CRAN:
install.packages("ganDataModel")

Install from Github:
library("remotes")
install_github("cran/ganDataModel")

Install by package version:
library("remotes")
install_version("ganDataModel", "1.1.7")



Attach the package and use:
library("ganDataModel")
Maintained by
Werner Mueller
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-07-16
Latest Update: 2023-05-07
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' .
How to cite:
Werner Mueller (2022). ganDataModel: Build a Metric Subspaces Data Model for a Data Source. R package version 1.1.7, https://cran.r-project.org/web/packages/ganDataModel. Accessed 06 Nov. 2024.
Previous versions and publish date:
1.0.2 (2022-07-16 10:20), 1.1.1 (2022-12-19 09:00), 1.1.2 (2023-03-05 14:50), 1.1.3 (2023-04-02 14:50), 1.1.4 (2023-05-07 23:00), 1.1.5 (2023-12-14 03:00), 1.1.6 (2024-01-21 16:10)
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