impute.val |
(numeric)
If something goes wrong during optimization (e.g. the learner crashes),
this value is fed back to the tuner, so the tuning algorithm does not abort.
Imputation is only active if on.learner.error is configured not to stop in configureMlr.
It is not stored in the optimization path, an NA and a corresponding error message are
logged instead.
Note that this value is later multiplied by -1 for maximization measures internally, so you
need to enter a larger positive value for maximization here as well.
Default is the worst obtainable value of the performance measure you optimize for when
you aggregate by mean value, or Inf instead.
For multi-criteria optimization pass a vector of imputation values, one for each of your measures,
in the same order as your measures.
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log.fun |
(function | character(1))
Function used for logging. If set to “default” (the default), the evaluated design points, the resulting
performances, and the runtime will be reported.
If set to “memory” the memory usage for each evaluation will also be displayed, with character(1) small increase
in run time.
Otherwise character(1) function with arguments learner, resampling, measures,
par.set, control, opt.path, dob, x, y, remove.nas,
stage and prev.stage is expected.
The default displays the performance measures, the time needed for evaluating,
the currently used memory and the max memory ever used before
(the latter two both taken from gc).
See the implementation for details.
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