Regression.Select.MinAvgErr.Config-class

Configuration class for the "MinAvgErr" specialization of the "Regression.Select.Fit" operation in EnsembleBase package. This operation selects the base learner configuration with minimum average error across repeated cross-validation runs.

classes

Extends the base classes and methods of EnsembleBase package for cross-validation-based integration of base learners. Default implementation calculates average of repeated CV errors, and selects the base learner / configuration with minimum average error. The package takes advantage of the file method provided in EnsembleBase package for writing estimation objects to disk in order to circumvent RAM bottleneck. Special save and load methods are provided to allow estimation objects to be saved to permanent files on disk, and to be loaded again into temporary files in a later R session. The package can be extended, e.g. by adding variants of the current implementation.

Alireza Mahani

EnsembleCV

Extensible Package for Cross-Validation-Based Integration of
Base Learners

Regression.Select.MinAvgErr.Config-class function

Objects can be created by calls of the form <code>new("Regression.Select.MinAvgErr.Config", ...)</code>.

Objects from the Class

<dl>
 <dt><code>instance.list</code>:</dt>
<dd>Object of class <code>Instance.List-class</code>, containing a list of base learners to train.</dd> <dt><code>errfun</code>:</dt>
<dd>Object of class <code>"function"</code>, the error metric to use for ranking base learner performances.</dd> 
</dl>

Slots

Class <code>"Regression.Select.Config-class"</code>, directly.

Extends

<dl>
 <dt>Regression.Select.Fit</dt>
<dd><code>signature(object = "Regression.Select.MinAvgErr.Config")</code>: ...</dd> 
</dl>

Methods

Mansour T.A. Sharabiani, Alireza S. Mahani

Author

Class "Regression.Select.MinAvgErr.Config" — Regression.Select.MinAvgErr.Config-class

<dl>
 <dt><code>instance.list</code>:</dt>
<dd>Object of class <code>Instance.List-class</code>, containing a list of base learners to train.</dd>

 <dt><code>errfun</code>:</dt>
<dd>Object of class <code>"function"</code>, the error metric to use for ranking base learner performances.</dd>

 
</dl>

<dl>
 <dt>Regression.Select.Fit</dt>
<dd><code>signature(object = "Regression.Select.MinAvgErr.Config")</code>: ...</dd>

 
</dl>

Regression.Select.MinAvgErr.Config-class: Class `"Regression.Select.MinAvgErr.Config"`

Description

Arguments

Objects from the Class

Slots

Extends

Methods

Author