autoplot.ecr_single_objective_result

[<code>ecr_result</code>]
ecr result object.

object

[<code>logical(1)</code>]
Should the function itself with the population be plotted as well? Thinks makes
in particular sense with <code>complete.trace = FALSE</code> to see the progress.
Keep in mind, that this is possible only if the representation is &#147;float&#148;
and the objective function has at most two decision variables.
Default is <code>FALSE</code>.

show.process

[<code>logical(1)</code>]
Log-transform fitness values?
Default is <code>FALSE</code>.

log.fitness

[<code>logical(1)</code>]
Direct show the plot with the fitness for all generations.
Default is <code>TRUE</code>.

complete.trace


Call this function on the result object of an <code><a rd-options="" href="/link/doTheEvolution?package=ecr&version=1.0.1" data-mini-rdoc="ecr::doTheEvolution">doTheEvolution</a></code>
function call to visualize the optimization trace.


Provides a powerful framework for evolutionary
computing in R. The user can easily construct powerful evolutionary algorithms
for tackling both single- and multi-objective problems by plugging in different
predefined evolutionary building blocks, e. g., operators for mutation,
recombination and selection with just a few lines of code. Your problem
cannot be easily solved with a standard EA which works on real-valued vectors,
permutations or binary strings? No problem, 'ecr' has been developed with that in
mind. Extending the framework with own operators is also possible. Additionally
there are various comfort functions, like monitoring, logging and more.

Jakob Bossek

Evolutionary Computing in R

autoplot.ecr_single_objective_result function


Call this function on the result object of an <code><a rd-options='' href='doTheEvolution'>doTheEvolution</a></code>
function call to visualize the optimization trace.


autoplot.ecr_single_objective_result: Plot optimization trace.

Description

Usage

Arguments

Value