aggregation.apply: apply aggregation function
In collinleiber/benchmarkVis: Benchmark result visualisation

do aggregation and return a new data table. the groupby columns must include problem and algorithm

1	aggregation.apply(groupby, aggfun, aggcol, dt)

`groupby`	the list of columns name that will be grouped
`aggfun`	the function to aggregate with
`aggcol`	the list of columns name that will be aggregated
`dt`	the input dataframe

a dataframe

1	aggregation.apply(groupby= c("problem", "algorithm"), aggfun= c("mean"), aggcol= c("measure.mmce.test.mean", "measure.ber.test.mean"), dt= mlr.benchmark.example)