- 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
- 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 now reset to NULL if 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
- 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
-
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.
- Work with new mlr3 version 0.1.5 (handling of character columns changed)
- Better html graphics for linear Graphs
- New PipeOps:
- PipeOpEncodeImpact
- Changed PipeOp Behaviour:
- PipeOpEncode: handle NAs
- Initial upload to CRAN.