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mlr3pipelines 0.7.1-9000

  • New parameter no_collapse_above_absolute in 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)

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 0.5.2

  • 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

  • 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

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

mlr3pipelines 0.5.0-1

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

mlr3pipelines 0.5.0

  • 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

  • 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

  • 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

  • $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

  • 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

  • Fix numerics problem in tests

mlr3pipelines 0.3.6

  • 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

  • Fixed: Compatibility with upcoming mlr3 version.

mlr3pipelines 0.3.5

  • 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

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

mlr3pipelines 0.3.3

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

mlr3pipelines 0.3.2

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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.