generateDesignOfDefaults

<p>[<code><a rd-options="" href="/link/ParamSet?package=ParamHelpers&version=1.12" data-mini-rdoc="ParamHelpers::ParamSet">ParamSet</a></code>]
Parameter set.</p>

par.set

<p>[<code>logical(1)</code>]
Transform all parameters by using theirs respective transformation functions.
Default is <code>FALSE</code>.</p>

trafo

<p>The following types of columns are created:</p><table><tr><td>
 numeric(vector)   </td>
<td>  <code>numeric</code>  </td>
</tr><tr><td>
 integer(vector)   </td>
<td>  <code>integer</code>  </td>
</tr><tr><td>
 discrete(vector)  </td>
<td>  <code>factor</code> (names of values = levels) </td>
</tr></table><p>This will create a design containing only one point at the default values of the supplied param set.
In most cases you will combine the resulting <code>data.frame</code> with a different generation function
e.g. <code><a rd-options="" href="/link/generateDesign?package=ParamHelpers&version=1.12" data-mini-rdoc="ParamHelpers::generateDesign">generateDesign</a></code>, <code><a rd-options="" href="/link/generateRandomDesign?package=ParamHelpers&version=1.12" data-mini-rdoc="ParamHelpers::generateRandomDesign">generateRandomDesign</a></code> or <code><a rd-options="" href="/link/generateGridDesign?package=ParamHelpers&version=1.12" data-mini-rdoc="ParamHelpers::generateGridDesign">generateGridDesign</a></code>.
This is useful to force an evaluation at the default location of the parameters while still generating
a design.
Parameters default values, whose conditions (<code>requires</code>) are not fulfilled will be set to <code>NA</code>
in the result.</p>

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.

Jakob Richter

ParamHelpers

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

Bernd Bischl

Michel Lang

Jakob Bossek

Daniel Horn

Karin Schork

Pascal Kerschke

generateDesignOfDefaults function

<p>[<code><a rd-options='' href='ParamSet'>ParamSet</a></code>]
Parameter set.</p>

<p>The following types of columns are created:</p><table><tr><td>
 numeric(vector)   </td>
<td>  <code>numeric</code>  </td>
</tr><tr><td>
 integer(vector)   </td>
<td>  <code>integer</code>  </td>
</tr><tr><td>
 discrete(vector)  </td>
<td>  <code>factor</code> (names of values = levels) </td>
</tr></table><p>This will create a design containing only one point at the default values of the supplied param set.
In most cases you will combine the resulting <code>data.frame</code> with a different generation function
e.g. <code><a rd-options='' href='generateDesign'>generateDesign</a></code>, <code><a rd-options='' href='generateRandomDesign'>generateRandomDesign</a></code> or <code><a rd-options='' href='generateGridDesign'>generateGridDesign</a></code>.
This is useful to force an evaluation at the default location of the parameters while still generating
a design.
Parameters default values, whose conditions (<code>requires</code>) are not fulfilled will be set to <code>NA</code>
in the result.</p>

generateDesignOfDefaults: Generates a design with the defaults of a parameter set.

Description

Usage

Arguments

Value

numeric(vector)	`numeric`
integer(vector)	`integer`
discrete(vector)	`factor` (names of values = levels)