gdGetRow

Get a row in generative data for a row index

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 evaluation, missing data completion and data classification. 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>.

Werner Mueller

ganGenerativeData

Generate Generative Data for a Data Source

gdGetRow function

<dl><dt>index</dt>
<dd>Index of row</dd></dl>

Arguments

Get a row in generative data — gdGetRow

<dl>

<dt>index</dt>
<dd>Index of row</dd>

</dl>

gdGetRow: Get a row in generative data

Description

Usage

Value

Arguments

Examples