mlr3pipelines 0.9.0

• Breaking change: Removed initialization of PipeOpImputeConstant's constant hyperparameter since it was incompatible with other defaults and would lead to not recommended usage (creating an empty level).
• Removed compatibility for old paradox versions pre-1.0.0.
• Added empty_level_control argument to PipeOpImpute allowing control over edge cases for factor/ordered columns.
• Set new construction argument empty_level_control to "param" for PipeOpImputeOOR and to "always" for PipeOpImputeConstant.
• Untrained PipeOps that take NULL as input during training now automatically perform training during prediction.
• PipeOpImputeConstant, PipeOpImputeMode, PipeOpImputeOOR, and PipeOpImputeLearner can now handle factor or ordered features with zero levels.
• PipeOpImputeConstant now gives a more informative error message if check_levels is TRUE and a new level would be created through imputation.
• Fix: PipeOpImputeOOR now imputes ".MISSING" for factor/ordered features with only NAs instead of sampling from the feature's levels.
• Fix: PipeOpImputeLearner no longer adds "factor" or "ordered" levels for these feature types arbitrarily and instead updates levels correctly in certain edge-cases.
• Fixed the error message for unexpected Multiplicities in the input and output type checking during PipeOps training and prediction.
• Fixed a grammatical error in PipeOp's error message wrapper: now correctly says "This happened in ...".

mlr3pipelines 0.8.0

• Added missing error for predicting with untrained PipeOps / Graphs.
• Fix: Corrected typo in the hyperparameter name use_parallel of PipeOpVtreat.
• Fix: Do not overwrite initial hyperparameter settings of bbotk::OptimizerBatchNLoptr in LearnerClassifAvg / LearnerRegrAvg's internal optimize_weights_learneravg function.
• Added new convenience function preproc() for easier training of or prediction with PipeOps or Graphs.
• Fix: PipeOpVtreat, PipeOpEncodeImpact, and PipeOpEncodeLmer now accept the more precise TaskSupervised instead of Task as input for training and prediction.
• Docs: Added missing documentation for the task_type of the input and output channels of PipeOps that inherit from PipeOpTaskPreproc and set a non-default task_type.
• Fix: PipeOpEncodeLmer, PipeOpADAS, PipeOpBLSmote, PipeOpSmote, and PipeOpSmoteNC no longer throw an error in case of empty target levels during training.
• Fix: PipeOpClassBalancing now handles unseen target levels by ignoring them during upsampling instead of producing NAs.

mlr3pipelines 0.7.2

• 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.

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().

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")

mlr3pipelines 0.6.0

• Compatibility with new bbotk release.
• Added marshaling support to GraphLearner
• Support internal tuning and validation

mlr3pipelines 0.1.2

• Work with new mlr3 version 0.1.5 (handling of character columns changed)

mlr3pipelines 0.1.1

• Better html graphics for linear Graphs
• New PipeOps:
  • PipeOpEncodeImpact
• Changed PipeOp Behaviour:
  • PipeOpEncode: handle NAs

mlr3pipelines 0.1.0

Initial upload to CRAN.