task.add.random.cols

<code>[Task]</code> the input task.

task

<code>[integer(1)]</code> number of noise features to add.

<code>[function]</code> function <code>n</code> -&gt; <code>numeric(n)</code> that samples
random noise features.

dist

Adds <code>num</code> new features sampled from <code>dist</code> to <code>task</code>.
New features are inserted at random positions in the task
and named <code>RANDOM.1</code>...<code>RANDOM.[num]</code>
The returned <code>Task</code> has a <code>$orig.features</code> which
is a logical vector indicating the features that were originally
in the <code>Task</code>.
If the <code>$orig.features</code> slot is already present in
the input <code>task</code>, then the output will have added <code>FALSE</code> entries at
appropriate positions.

Performs simultaneous hyperparameter tuning and
feature selection through both single-objective and multi-objective
optimization as described in Binder, Moosbauer et al. (2019) <arXiv:1912.12912>.
Uses the 'ecr'-package as basis but adds mixed integer
evolutionary strategies and multi-fidelity functionality as well as operators
specific for the problem of feature selection.

Martin Binder

mosmafs

Multi-Objective Simultaneous Model and Feature Selection

Susanne Dandl

Julia Moosbauer

task.add.random.cols function

<dl><dt>task</dt>
<dd><code>[Task]</code> the input task.</dd>
<dt>num</dt>
<dd><code>[integer(1)]</code> number of noise features to add.</dd>
<dt>dist</dt>
<dd><code>[function]</code> function <code>n</code> -&gt; <code>numeric(n)</code> that samples
random noise features.</dd></dl>

Arguments

Add Sampled Noise-Features to Task — task.add.random.cols

<dl>

<dt>task</dt>
<dd><code>[Task]</code> the input task.</dd>


<dt>num</dt>
<dd><code>[integer(1)]</code> number of noise features to add.</dd>


<dt>dist</dt>
<dd><code>[function]</code> function <code>n</code> -&gt; <code>numeric(n)</code> that samples
random noise features.</dd>

</dl>

task.add.random.cols: Add Sampled Noise-Features to Task

Description

Usage

Value

Arguments

See Also