gdKNearestNeighbors

Search for k nearest neighbors in normalized generative data for a data record.
When the data record contains NA values only the non-NA values are considered in search.
By default a linear search is performed. When a search tree is used search is performed on a tree
which is built once in the first function call.
Building a tree is also triggered when NA values in data records change in subsequent function calls.

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

gdKNearestNeighbors function

<dl><dt>dataRecord</dt>
<dd>List containing an unnormalized data record</dd>
<dt>k</dt>
<dd>Number of nearest neighbors</dd>
<dt>useSearchTree</dt>
<dd>Boolean value indicating if a search tree should be used.</dd></dl>

Arguments

Search for k nearest neighbors — gdKNearestNeighbors

<dl>

<dt>dataRecord</dt>
<dd>List containing an unnormalized data record</dd>


<dt>k</dt>
<dd>Number of nearest neighbors</dd>


<dt>useSearchTree</dt>
<dd>Boolean value indicating if a search tree should be used.</dd>

</dl>

gdKNearestNeighbors: Search for k nearest neighbors

Description

Usage

Value

Arguments

Examples