reduceBatchmarkResults: Reduce results of a batch-distributed benchmark.
In Najah-lshanableh/R-data-mining2: Machine Learning in R

This creates a BenchmarkResult from a ExperimentRegistry. To setup the benchmark have a look at batchmark.

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reduceBatchmarkResults(ids = NULL, keep.pred = TRUE,
  show.info = getMlrOption("show.info"),
  reg = batchtools::getDefaultRegistry())

`ids`	[`data.frame` or `integer`] A `data.frame` (or `data.table`) with a column named “job.id”. Alternatively, you may also pass a vector of integerish job ids. If not set, defaults to all jobs.
`keep.pred`	[`logical(1)`] Keep the prediction data in the `pred` slot of the result object. If you do many experiments (on larger data sets) these objects might unnecessarily increase object size / mem usage, if you do not really need them. In this case you can set this argument to `FALSE`. Default is `TRUE`.
`show.info`	[`logical(1)`] Print verbose output on console? Default is set via `configureMlr`.
`reg`	[`ExperimentRegistry`] Registry, created by `makeExperimentRegistry`. If not explicitly passed, uses the last created registry.