plotEAF

Can be used to plot OptPaths where information for bi-objective
evaluation was logged for repeated runs of different algorithmic runs.
Pretty directly calls <code>eaf::eafplot()</code>.

Functions for parameter descriptions and operations in
black-box optimization, tuning and machine learning. Parameters can be
described (type, constraints, defaults, etc.), combined to parameter
sets and can in general be programmed on. A useful OptPath object
(archive) to log function evaluations is also provided.

Martin Binder

ParamHelpers

Helpers for Parameters in Black-Box Optimization, Tuning and
Machine Learning

Bernd Bischl

Michel Lang

Jakob Richter

Jakob Bossek

Daniel Horn

Karin Schork

Pascal Kerschke

plotEAF function

<dl><dt>opt.paths</dt>
<dd>(<code>list</code>) 
List of list of <code>OptPath</code> objects. First index is the algorithm / major
variation in the experiment, second index is the index of the replicated
run.</dd>
<dt>xlim</dt>
<dd>(<code>numeric(2)</code>) 
The x limits (x1, x2) of the plot.</dd>
<dt>ylim</dt>
<dd>(<code>numeric(2)</code>) 
The y limits (y1, y2) of the plot.</dd>
<dt>...</dt>
<dd>(any) 
Passed on to <code>eaf::eafplot()</code>.</dd></dl>

Arguments

Plots attainment functions for data stored in multiple OptPaths. — plotEAF

<dl>

<dt>opt.paths</dt>
<dd>(<code>list</code>) 
List of list of <code>OptPath</code> objects. First index is the algorithm / major
variation in the experiment, second index is the index of the replicated
run.</dd>


<dt>xlim</dt>
<dd>(<code>numeric(2)</code>) 
The x limits (x1, x2) of the plot.</dd>


<dt>ylim</dt>
<dd>(<code>numeric(2)</code>) 
The y limits (y1, y2) of the plot.</dd>


<dt>...</dt>
<dd>(any) 
Passed on to <code>eaf::eafplot()</code>.</dd>

</dl>

plotEAF: Plots attainment functions for data stored in multiple OptPaths.

Description

Usage

Value

Arguments