Package: ganGenerativeData 2.0.2

Werner Mueller

ganGenerativeData: Generate Generative Data for a Data Source

Generative Adversarial Networks are applied to generate generative data for a data source. A generative model consisting of a generator and a discriminator network is trained. During iterative training the distribution of generated data is converging to that of the data source. Direct applications of generative data are the created functions for data classifying and missing data completion. A software service for accelerated training of generative models on graphics processing units is available. Reference: Goodfellow et al. (2014) <doi:10.48550/arXiv.1406.2661>.

Authors:Werner Mueller

ganGenerativeData_2.0.2.tar.gz
ganGenerativeData_2.0.2.tar.gz(r-4.5-noble)ganGenerativeData_2.0.2.tar.gz(r-4.4-noble)
ganGenerativeData.pdf |ganGenerativeData.html✨
ganGenerativeData/json (API)

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30 exports 1 stars 1.00 score 36 dependencies 5 scripts 414 downloads

Last updated 3 months agofrom:5f5a079915. Checks:OK: 2. Indexed: yes.

Exports:dsActivateColumnsdsCreateWithDataFramedsDeactivateColumnsdsGetActiveColumnNamesdsGetInactiveColumnNamesdsGetNumberOfRowsdsGetRowdsReaddsWritegdCalculateDensityValuegdCalculateDensityValueQuantilegdCalculateDensityValuesgdCompletegdGenerategdGenerateParametersgdGetNumberOfRowsgdGetRowgdKNearestNeighborsgdPlotDataSourceParametersgdPlotParametersgdPlotProjectiongdReadgdServiceDeletegdServiceGetGenerativeDatagdServiceGetGenerativeModelgdServiceGetStatusgdServiceTraingdTraingdTrainParametersgdWriteSubset

Dependencies:askpassbackportsbase64enccliconfigcurlglueherehttrjsonlitelatticelifecyclemagrittrMatrixmimeopensslpngprocessxpsR6rappdirsRcppRcppTOMLreticulaterlangrprojrootrstudioapisystensorflowtfautographtfrunstidyselectvctrswhiskerwithryaml