gdWriteSubset

Write subset of randomly selected rows of generative data

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

gdWriteSubset function

<dl><dt>fileName</dt>
<dd>Name of subset generative data file</dd>
<dt>percent</dt>
<dd>Percent of randomly selected rows</dd></dl>

Arguments

Write subset of generative data — gdWriteSubset

<dl>

<dt>fileName</dt>
<dd>Name of subset generative data file</dd>


<dt>percent</dt>
<dd>Percent of randomly selected rows</dd>

</dl>

gdWriteSubset: Write subset of generative data

Description

Usage

Value

Arguments

Examples