Releases · mlr-org/mlr3pipelines

07 Mar 22:39

mb706

v0.7.2

40ad65b

mlr3pipelines 0.7.2 Latest

Latest

New parameter no_collapse_above_absolute for PipeOpCollapseFactors / po("collapse_factors").
Fix: PipeOpCollapseFactors now correctly collapses levels of ordered factors.
Fix: LearnerClassifAvg and LearnerRegrAvg hyperparameters get the "required" tag.
New parameter use_groups (default TRUE) for PipeOpSubsampling to respect grouping (changed default behaviour for grouped data)
New parameter new_role_direct for PipeOpColRoles / po("colroles") to change column roles by role instead of by column.
Dictionary sugar functions po() / pos() / ppl() / ppls() now make suggestions for entries in both mlr_pipeops as well as mlr_graphs when an object by the given name could not be found in the respective dictionary.
New PipeOp PipeOpDecode / po("decode") to reverse one-hot or treatment encoding.
Fix: Columns that are feature and something else no longer lose the other column role during training or predicting of PipeOps inheriting from PipeOpTaskPreproc.
Fix: Made tests for PipeOpBLSmote deterministic.
Fix: Corrected hash calculation for PipeOpFilter.
New PipeOps PipeOpEncodePLQuantiles and PipeOpEncodePLTree that implement piecewise linear encoding with two different binning methods.
Compatibility with new R6 release.
Docs: Performed cleanup and standardization.
Docs: Performed cleanup of reference index page on website.
Docs: Fixed parsing of examples on website for PipeOpNMF and PipeOpLearnerPICVPlus.
Fix: PipeOpTargetMutate and PipeOpTargetTrafoScaleRange no longer drop unseen factor levels of features or targets during train and predict.
Simplified parameter checks and added internal type checking for PipeOpTargetMutate.

Assets 3

15 Nov 10:34

mb706

v0.7.1

1566ae6

mlr3pipelines 0.7.1

Compatibility fix for upcoming mlr3
New down-sampling PipeOps for inbalanced data: PipeOpTomek / po("tomek") and PipeOpNearmiss / po("nearmiss")
New PipeOp PipeOpLearnerPICVPlus / po("learner_pi_cvplus")
New PipeOp for Quantile Regression PipeOpLearnerQuantiles / po(learner_quantiles)
GraphLearner has new active bindings/methods as shortcuts for active bindings/methods of the underlying Graph:
$pipeops, $edges, $pipeops_param_set, and $pipeops_param_set_values as well as $ids() and $plot().

Assets 3

29 Sep 17:52

mb706

v0.7.0

b3551e6

mlr3pipelines 0.7.0

New PipeOp PipeOpRowApply / po("rowapply")
Empty PipeOp IDs now explicitly forbidden.
Bugfix: Graph$tran() / Graph$predict() with single_input = FALSE now correctly handles PipeOps with multiple inputs.
GraphLearner$base_learner() now works with PipeOpBranch, and is generally more robust.
GraphLearner now supports $importance, $selected_features(), $oob_error(), and $loglik().
These are computed from the underlying Learner.
GraphLearner$impute_selected_features option added:
$selected_features() is reported even if the underlying base learner does not report it; in this case, the full feature set as seen by that learner is returned.
GraphLearner$predict_type handling more robust now.
PipeOpThreshold and PipeOpTuneThreshold now have the $predict_type "prob".
They can be set to "response", in which case the probability predictions are discarded, potentially saving memory.
Bugfix for handling multiplicities in PipeOps with vararg channels.
Bugfix: PipeOpImputeOOR now retains the .MISSING level in factors during prediction that were imputed during training, but had no missing values during prediction.
as_data_table(po()) now works even when some PipeOps can not be constructed.
For these PipeOps, NA is reported in most columns.
Compatibility with upcoming mlr3 release.
New PipeOps for handling inbalanced data: PipeOpADAS / po("adas"), PipeOpBLSmote / po("blsmote") and PipeOpSmoteNC / po("smotenc")