Usually used for 1D or 2D examples,
useful for figuring out how stuff works and for teaching purposes.
Currently only parameter spaces with numerical parameters are supported.
For visualization, run
plotExampleRun on the resulting object.
What is displayed is documented here:
Rendering the plots without displaying them is possible via the function
Please note the following things:
- The true objective function (and later everything which is predicted from our surrogate model)
is evaluated on a regular spaced grid. These evaluations are stored in the result object.
You can control the resolution of this grid via
Parallelization of these evaluations is possible with the R package parallelMap on the level
- In every iteration the fitted, approximating surrogate model is stored in the result object
control) so we can later visualize it quickly.
- The global optimum of the function (if defined) is extracted from the passed smoof function.
- If the passed objective function
fun does not provide the true, unnoisy objective function
some features will not be displayed (for example the gap between the best point so far and the global optimum).
exampleRun( fun, design = NULL, learner = NULL, control, points.per.dim = 50, noisy.evals = 10, show.info = getOption("mlrMBO.show.info", TRUE) )