recIntIntermediate

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

recIntIntermediate function

<dl><dt>inds</dt>
<dd><code>[inds]</code> parents, i.e., list of exactly two integer vectors
of equal length.</dd>
<dt>...</dt>
<dd>further arguments passed on to the method.</dd>
<dt>lower</dt>
<dd><code>[integer]</code> vector of minimal values for each parameter of the
decision space.</dd>
<dt>upper</dt>
<dd><code>[integer]</code> vector of maximal values for each parameter of the
decision space.</dd></dl>

Arguments

Integer Intermediate Recombinator — recIntIntermediate

<dl>

<dt>inds</dt>
<dd><code>[inds]</code> parents, i.e., list of exactly two integer vectors
of equal length.</dd>


<dt>...</dt>
<dd>further arguments passed on to the method.</dd>


<dt>lower</dt>
<dd><code>[integer]</code> vector of minimal values for each parameter of the
decision space.</dd>


<dt>upper</dt>
<dd><code>[integer]</code> vector of maximal values for each parameter of the
decision space.</dd>

</dl>

recIntIntermediate: Integer Intermediate Recombinator

Description

Usage

Value

Arguments

See Also