Regression.Sweep.CV.FitObj-class

Class containing output of <code>Regression.Sweep.CV.Fit</code> function.

classes

Extending the base classes and methods of EnsembleBase package for Penalized-Regression-based (Ridge and Lasso) integration of base learners. Default implementation uses cross-validation error to choose the optimal lambda (shrinkage parameter) for the final predictor. 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. Users and developers can extend the package by extending the generic methods and classes provided in EnsembleBase package as well as this package.

Alireza Mahani

EnsemblePenReg

Extensible Classes and Methods for Penalized-Regression-Based
Integration of Base Learners

Regression.Sweep.CV.FitObj-class function

Objects can be created by calls of the form <code>new("Regression.Sweep.CV.FitObj", ...)</code>.

Objects from the Class

<dl>
 <dt><code>sweep.list</code>:</dt>
<dd>Object of class <code>"list"</code>, list of length equal to number of folds in <code>partition</code>. Each element of list is contains the output of <code>Regression.Sweep.Fit</code> and has class <code>Regression.Sweep.FitObj</code>.</dd> <dt><code>pred</code>:</dt>
<dd>Object of class <code>"matrix"</code>, containing the matrix of predictions from this operation.</dd> <dt><code>partition</code>:</dt>
<dd>Object of class <code>"OptionalInteger"</code>, data partition used to perform CV sweep.</dd> 
</dl>

Slots

Mansour T.A. Sharabiani, Alireza S. Mahani

Author

Class "Regression.Sweep.CV.FitObj" — Regression.Sweep.CV.FitObj-class

<dl>
 <dt><code>sweep.list</code>:</dt>
<dd>Object of class <code>"list"</code>, list of length equal to number of folds in <code>partition</code>. Each element of list is contains the output of <code>Regression.Sweep.Fit</code> and has class <code>Regression.Sweep.FitObj</code>.</dd>

 <dt><code>pred</code>:</dt>
<dd>Object of class <code>"matrix"</code>, containing the matrix of predictions from this operation.</dd>

 <dt><code>partition</code>:</dt>
<dd>Object of class <code>"OptionalInteger"</code>, data partition used to perform CV sweep.</dd>

 
</dl>

Regression.Sweep.CV.FitObj-class: Class `"Regression.Sweep.CV.FitObj"`

Description

Arguments

Objects from the Class

Slots

Author

See Also