dmGetContainedInMetricSubspaces

Determine in which metric subspaces in a data model a data record is contained.

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>.

Werner Mueller

ganDataModel

Build a Metric Subspaces Data Model for a Data Source

dmGetContainedInMetricSubspaces function

<dl><dt>dataRecord</dt>
<dd>List of a data record</dd></dl>

Arguments

Get metric subspaces in which a data record is contained — dmGetContainedInMetricSubspaces

<dl>

<dt>dataRecord</dt>
<dd>List of a data record</dd>

</dl>

dmGetContainedInMetricSubspaces: Get metric subspaces in which a data record is contained

Description

Usage

Value

Arguments

Examples