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].
- Version1.1.7
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release07/21/2024
Team
Werner Mueller
MaintainerShow author details
Insights
Last 30 days
This package has been downloaded 311 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.
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Last 365 days
This package has been downloaded 3,441 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 24, 2024 with 38 downloads.
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Dependencies
- Imports2 packages
- Linking To1 package