FSelectorRFEsupports fraction of features to retain in each iteration (
feature_fraction), number of features to remove in each iteration (
feature_number) and vector of number of features to retain in each iteration (
AutoFSelectis renamed to
as.data.table(rr)$learner[]$fselect_resultmust be used now.
store_fselect_instancemust be set as a parameter during initialization.
PipeOpSelectis internally used for task subsetting.
ArchiveFSelectnow which stores the benchmark result in
$benchmark_result. This change removed the resample results from the archive but they can be still accessed via the benchmark result.