Skip to contents

Changelog

Source: NEWS.md

mlr3pipelines 0.10.0-9000

  • Fix: Made FilterEnsemble tests deterministic and more robust.
  • Fix: Made tests for PipeOpLearnerCV deterministic.
  • feat: All imputation PipeOps now support feature types Date and POSIXct.
  • Fix: PipeOpTextVectorizer now uses coercion to TsparseMatrix instead of deprecated dgTMatrix to avoid Matrix deprecation warnings.
  • New method $predict_newdata_fast() for GraphLearner. Note that currently this is only a thin wrapper around $predict_newdata() to maintain compatibility, but in the future it may get optimized to enable faster predictions on new data.
  • feat: PipeOpRenameColumns’s hyperparameter renaming can now also take a function transforming old column names to new column names.
  • feat: Added new hyperparameters filter_score_transform, result_score_transform, and aggregator to FilterEnsemble. BREAKING CHANGE: The default behavior for handling NA scores in the aggregation has changed. Previously, NA scores were simply ignored and weights were not changed. Now, weighted.mean is used, which normalizes the weights for all non-NA scores.

mlr3pipelines 0.10.0

CRAN release: 2025-11-07

  • Pretty-printing some info using the cli package now.
  • New PipeOp PipeOpInfo prints or logs info about objects passing through.
  • New Pipeop PipeOpIsomap implements isomap embedding from dimRed::embed
  • feat: allow dates in datefeatures pipe op and use data.table for date feature generation.
  • feat: PipeOpLearnerCV can reuse the cross-validation models during prediction by averaging their outputs (resampling.predict_method = "cv_ensemble").
  • feat: PipeOpRegrAvg gets new se_aggr, se_aggr_rho, prob_aggr, and prob_aggr_eps hyperparameters and now allows different forms of prob / SE aggregation.
  • feat: FilterEnsemble implements Binder et al. (2020) Multi-Objective Hyperparameter Tuning and Feature Selection using Filter Ensembles
  • Fix: PipeOpRemoveConstants now avoids integer overflow when evaluating relative tolerances for near-integer.max data.
  • Fix: Added support for internal validation tasks to PipeOpFeatureUnion.
  • Fix: Added internal workaround for PipeOpNMF attaching Biobase, BiocGenerics, and generics to the search path during training, prediction or when printing its $state.
  • Compatibility with new testthat version 3.3.0

mlr3pipelines 0.9.0

CRAN release: 2025-07-31

  • 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

CRAN release: 2025-06-17

  • 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

CRAN release: 2025-03-07

  • 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

CRAN release: 2024-11-14

  • 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

CRAN release: 2024-09-24

  • 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

CRAN release: 2024-07-01

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

mlr3pipelines 0.5.2

CRAN release: 2024-04-23

  • Added new ppl("convert_types").
  • Minor documentation fixes.
  • Test helpers are now available in inst/. These are considered experimental and unstable.

mlr3pipelines 0.5.1

CRAN release: 2024-03-26

  • Changed the ID of PipeOpFeatureUnion used in ppl("robustify") and ppl("stacking").
  • pipeline_bagging() gets the replace argument (old behaviour FALSE by default).
  • Feature: The $add_pipeop() method got an argument clone (old behaviour TRUE by default).
  • Bugfix: PipeOpFeatureUnion in some rare cases dropped variables called "x".
  • Compatibility with upcoming paradox release.

mlr3pipelines 0.5.0-2

CRAN release: 2023-12-08

  • Avoid unnecessarily large serializations of ppl("robustify") pipelines.
  • Made tests and examples compatible with mlr3 update.

mlr3pipelines 0.5.0-1

CRAN release: 2023-05-22

  • Bugfix: PipeOpTuneThreshold was not overloading the correct .train and .predict functions.

mlr3pipelines 0.5.0

CRAN release: 2023-05-22

  • New way of computing $hash and $phash for GraphLearner and all PipeOps. This could break users that inherit from PipeOp and make use of $hash in the future (but is ultimately in their interest!).
  • Neater plots.
  • Bugfix: phash of GraphLearner now considers content of Graph, not only IDs.
  • One vignette removed for version 0.1.3 added back here. Welcome home!
  • Bugfix: Make Graph work that have PipeOps with more than one output, where one output was linked to multiple inputs.

mlr3pipelines 0.4.3

CRAN release: 2023-03-23

  • po(), pos() can now construct PipeOps with ID postfix _<number> to avoid ID clashes.
  • GraphLearner now has method $base_learner() that returns the underlying Learner, if it can be found by a simple heuristic.
  • Fix S3 function signatures

mlr3pipelines 0.4.2

CRAN release: 2022-09-20

  • Documentation: Clarified PipeOpHistBin operation.
  • Documentation: Fixed PipeOpPCA documentation of center default.
  • Added $label active binding, setting it to the help()-page title by default.
  • Made tests compatible with upcoming mlr3misc update.

mlr3pipelines 0.4.1

CRAN release: 2022-05-15

  • $help() function for all PipeOps as well as Graph, GraphLearner and all Learners.
  • GraphLearner can be created without cloning Graph (for internal use).
  • predict.Graph throws helpful error when it cannot create a fitting Task.
  • PipeOpLearner packages slot is set to the Learner’s packages.
  • Bugfix: PipeOp train() and predict() report correct channel name when output has wrong type.
  • Bugfix: More accurate type inference when constructing Graphs.
  • Stability fix for interaction with packages such as mlr3spatiotempcv that extend existing Task types.

mlr3pipelines 0.4.0

CRAN release: 2021-11-15

  • New operator %>>!% that modifies Graphs in-place.
  • New methods chain_graphs(), concat_graphs(), Graph$chain() as alternatives for %>>% and %>>!%.
  • New methods pos() and ppls() which create lists of PipeOps/Graphs and can be seen as “plural” forms of po() and ppl().
  • po() S3-method for PipeOp class that clones a PipeOp object and optionally modifies its attributes.
  • Graph$add_pipeop() now clones the PipeOp being added.
  • Documentation: Clarified documentation about cloning of input arguments in several places.
  • Performance enhancements for Graph concatenation.
  • More informative error outputs.
  • New attribute graph_model in GraphLearner class, which gets the trained Graph.
  • as_learner() S3-method for PipeOp class that wraps a PipeOp in a Graph and turns that into a Learner.
  • Changed PipeOps:
    • PipeOpHistBin: renamed bins Param to breaks
    • PipeOpImputeHist: fix handling of integer features spanning the entire represented integer range
    • PipeOpImputeOOR: fix handling of integer features spanning the entire represented integer range
    • PipeOpProxy: Avoid unnecessary clone
    • PipeOpScale: Performance improvement

mlr3pipelines 0.3.6-1

CRAN release: 2021-10-06

  • Fix numerics problem in tests

mlr3pipelines 0.3.6

CRAN release: 2021-09-07

  • Bugfix: Make empty Multiplicities work (unless they are nested)
  • Fixed: Compatibility with upcoming bbotk version.
  • New mlr_graphs: pipeline_stacking
  • Added JMLR-Citation

mlr3pipelines 0.3.5-1

CRAN release: 2021-08-05

  • Fixed: Compatibility with upcoming mlr3 version.

mlr3pipelines 0.3.5

CRAN release: 2021-07-06

  • Changed PipeOp: PipeOpFilter gets additional filter.permuted hyperparameter.
  • Bugfix: Make add_edge of Graphs work with Multiplicities.
  • Bugfix: Make GraphLearner hash depend on id.
  • Documentation: Clarify documentation of LearnerAvg.
  • Internals: Using more idiomatic internal helper functions.
  • Compatibility with upcoming mlr3 version.

mlr3pipelines 0.3.4

CRAN release: 2021-03-05

  • Stability: PipeOps don’t crash when they have python/reticulate hyperparameter values.
  • Documentation: Titles of PipeOp documentation articles reworked.

mlr3pipelines 0.3.3

CRAN release: 2021-02-09

  • Bugfix: fix rare issue in randomized test
  • Compatibility with bbotk 0.3.0

mlr3pipelines 0.3.2

CRAN release: 2020-12-17

  • Bugfix: Make as.data.table(mlr_pipeops) work with paradox 0.6
  • Changed PipeOps:
    • PipeOpColApply: now allows for an applicator function with multiple columns as a return value; also inherits from PipeOpTaskPreprocSimple now

mlr3pipelines 0.3.1

CRAN release: 2020-11-16

  • Changed PipeOps:
    • PipeOpMissInd now also allows for setting type = integer
    • PipeOpNMF: now exposes all parameters previously in .options
  • Changed mlr_graphs:
    • pipeline_bagging now uses multiplicities internally
    • fix how pipeline_robustify determines the type of newly created columns when using PipeOpMissInd
    • PipeOpFeatureUnion: Fixed a minor bug when checking for duplicates
  • added an autotest for ParamSets of PipeOps: expect_valid_pipeop_param_set
  • More informative error message when PipeOp input value has wrong type
  • Fix automatic detection of R6 type hierarchy
  • Performance improvements for GraphLearner
  • GraphLearner allows custom id
  • Use parallel tests
  • Removed bibtex dependency

mlr3pipelines 0.3.0

CRAN release: 2020-09-13

  • compatibility with mlr3 0.6
  • NULL input channels accept any kind of input
  • print() method of Graphs now also allows for printing a DOT representation on the console
  • state of PipeOps is now reset to NULL when training fails
  • implemented as_learner.PipeOp
  • LearnerClassifAvg, LearnerRegrAvg use bbotk now
  • Changed PPLs:
    • fix how ppl_robustify detects whether a learner can handle factors
  • Changed PipeOps:
    • PipeOpTextVectorizer can now return an “integer sequence representation”.
  • New PipeOps:
    • PipeOpNMF
    • PipeOpColRoles
    • PipeOpVtreat
  • various bugfixes

mlr3pipelines 0.2.1

CRAN release: 2020-08-18

  • New feature: Multiplicities: implicit repetition of operations
  • new mlr_graphs:
    • pipeline_bagging
    • pipeline_branch
    • pipeline_greplicate
    • pipeline_robustify
    • pipeline_targettrafo
    • pipeline_ovr
  • New PipeOps:
    • PipeOpOVRSplit, PipeOpOVRUnite
    • PipeOpReplicate
    • PipeOpMultiplicityExply, PipeOpMultiplicityImply
    • PipeOpTargetTrafo, PipeOpTargetInvert
    • PipeOpTargetMutate
    • PipeOpTargetTrafoScaleRange
    • PipeOpProxy
    • PipeOpDateFeatures
    • PipeOpImputeConstant
    • PipeOpImputeLearner
    • PipeOpMode
    • PipeOpRandomResponse
    • PipeOpRenameColumns
    • PipeOpTextVectorizer
    • PipeOpThreshold
  • Renamed PipeOps:
    • PipeOpImputeNewlvl –> PipeOpImputeOOR (with additional functionality for continuous values)
  • Changed PipeOps:
    • PipeOpFeatureUnion: Bugfix: avoid silently overwriting features when names clash
    • PipeOpHistBin: Bugfix: handle test set data out of training set range
    • PipeOpLearnerCV: Allow returning trainingset prediction during train()
    • PipeOpMutate: Allow referencing newly created columns
    • PipeOpScale: Allow robust scaling
    • PipeOpLearner, PipeOpLearnerCV: learner_models for access to learner with model slot
  • New Selectors:
    • selector_missing
    • selector_cardinality_greater_than
  • NULL is neutral element of %>>%
  • PipeOpTaskPreproc now has feature_types slot
  • PipeOpTaskPreproc(Simple) internal API changed: use .train_task(), .predict_task(), .train_dt(), .predict_dt(), .select_cols(), .get_state(), .transform(), .get_state_dt(), .transform_dt() instead of the old methods without dot prefix
  • PipeOp now has tags slot
  • PipeOp internal API changed: use .train(), .predict() instead of train_internal(), predict_internal()
  • Graph new method update_ids()
  • Graph methods train(single_input = FALSE) and predict(single_input = FALSE) now handle vararg channels correctly.
  • Obsoleted greplicate(); use pipeline_greplicate / ppl("greplicate") instead.
  • po() now automatically converts Selector to PipeOpSelect
  • po() prints available mlr_pipeops dictionary content
  • mlr_graphs dictionary of useful Graphs, with short form accessor ppl()
  • Work with new mlr3 version 0.4.0

mlr3pipelines 0.1.3

CRAN release: 2020-04-06

  • small test fix for R 4.0 (necessary for stringsAsFactors option default change in 3.6 -> 4.0)
  • predict() generic for Graph
  • Migrated last vignette to “mlr3 Book”
  • Compact in-memory representation of R6 objects to save space when saving objects via saveRDS(), serialize() etc.

mlr3pipelines 0.1.2

CRAN release: 2019-12-10

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

mlr3pipelines 0.1.1

CRAN release: 2019-10-29

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

mlr3pipelines 0.1.0

CRAN release: 2019-10-06

  • Initial upload to CRAN.