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mlr3pipelines  

Preprocessing Operators and Pipelines for 'mlr3'
View on CRAN: Click here


Download and install mlr3pipelines package within the R console
Install from CRAN:
install.packages("mlr3pipelines")

Install from Github:
library("remotes")
install_github("cran/mlr3pipelines")

Install by package version:
library("remotes")
install_version("mlr3pipelines", "0.7.1")



Attach the package and use:
library("mlr3pipelines")
Maintained by
Martin Binder
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-06
Latest Update: 2023-05-22
Description:
Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
How to cite:
Martin Binder (2019). mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'. R package version 0.7.1, https://cran.r-project.org/web/packages/mlr3pipelines. Accessed 29 Jan. 2025.
Previous versions and publish date:
0.1.0 (2019-10-06 12:40), 0.1.1 (2019-10-29 08:00), 0.1.2 (2019-12-10 19:00), 0.1.3 (2020-04-06 11:00), 0.2.1 (2020-08-18 09:40), 0.3.0 (2020-09-13 23:50), 0.3.1 (2020-11-16 08:50), 0.3.2 (2020-12-18 00:40), 0.3.3 (2021-02-09 07:10), 0.3.4 (2021-03-05 23:10), 0.3.5-1 (2021-08-05 06:20), 0.3.5 (2021-07-06 06:50), 0.3.6-1 (2021-10-06 06:20), 0.3.6 (2021-09-07 19:30), 0.4.0 (2021-11-15 13:10), 0.4.1 (2022-05-15 20:20), 0.4.2 (2022-09-21 00:00), 0.4.3 (2023-03-23 18:00), 0.5.0-1 (2023-05-22 12:10), 0.5.0-2 (2023-12-08 23:20), 0.5.0 (2023-05-22 07:30), 0.5.1 (2024-03-26 20:50), 0.5.2 (2024-04-23 22:50), 0.6.0 (2024-07-01 15:30), 0.7.0 (2024-09-24 17:30)
Other packages that cited mlr3pipelines R package
View mlr3pipelines citation profile
Other R packages that mlr3pipelines depends, imports, suggests or enhances
Complete documentation for mlr3pipelines
Functions, R codes and Examples using the mlr3pipelines R package
Some associated functions: Graph . Multiplicity . NO_OP . PipeOp . PipeOpEnsemble . PipeOpImpute . PipeOpTargetTrafo . PipeOpTaskPreproc . PipeOpTaskPreprocSimple . Selector . add_class_hierarchy_cache . as.Multiplicity . as_graph . as_pipeop . assert_graph . assert_pipeop . chain_graphs . filter_noop . grapes-greater-than-greater-than-grapes . greplicate . gunion . is.Multiplicity . is_noop . mlr3pipelines-package . mlr_graphs . mlr_graphs_bagging . mlr_graphs_branch . mlr_graphs_greplicate . mlr_graphs_ovr . mlr_graphs_robustify . mlr_graphs_stacking . mlr_graphs_targettrafo . mlr_learners_avg . mlr_learners_graph . mlr_pipeops . mlr_pipeops_boxcox . mlr_pipeops_branch . mlr_pipeops_chunk . mlr_pipeops_classbalancing . mlr_pipeops_classifavg . mlr_pipeops_classweights . mlr_pipeops_colapply . mlr_pipeops_collapsefactors . mlr_pipeops_colroles . mlr_pipeops_copy . mlr_pipeops_datefeatures . mlr_pipeops_encode . mlr_pipeops_encodeimpact . mlr_pipeops_encodelmer . mlr_pipeops_featureunion . mlr_pipeops_filter . mlr_pipeops_fixfactors . mlr_pipeops_histbin . mlr_pipeops_ica . mlr_pipeops_imputeconstant . mlr_pipeops_imputehist . mlr_pipeops_imputelearner . mlr_pipeops_imputemean . mlr_pipeops_imputemedian . mlr_pipeops_imputemode . mlr_pipeops_imputeoor . mlr_pipeops_imputesample . mlr_pipeops_kernelpca . mlr_pipeops_learner . mlr_pipeops_learner_cv . mlr_pipeops_missind . mlr_pipeops_modelmatrix . mlr_pipeops_multiplicityexply . mlr_pipeops_multiplicityimply . mlr_pipeops_mutate . mlr_pipeops_nmf . mlr_pipeops_nop . mlr_pipeops_ovrsplit . mlr_pipeops_ovrunite . mlr_pipeops_pca . mlr_pipeops_proxy . mlr_pipeops_quantilebin . mlr_pipeops_randomprojection . mlr_pipeops_randomresponse . mlr_pipeops_regravg . mlr_pipeops_removeconstants . mlr_pipeops_renamecolumns . mlr_pipeops_replicate . mlr_pipeops_scale . mlr_pipeops_scalemaxabs . mlr_pipeops_scalerange . mlr_pipeops_select . mlr_pipeops_smote . mlr_pipeops_spatialsign . mlr_pipeops_subsample . mlr_pipeops_targetinvert . mlr_pipeops_targetmutate . mlr_pipeops_targettrafoscalerange . mlr_pipeops_textvectorizer . mlr_pipeops_threshold . mlr_pipeops_tunethreshold . mlr_pipeops_unbranch . mlr_pipeops_updatetarget . mlr_pipeops_vtreat . mlr_pipeops_yeojohnson . po . ppl . reexports . register_autoconvert_function . reset_autoconvert_register . reset_class_hierarchy_cache . 
Some associated R codes: Graph.R . GraphLearner.R . LearnerAvg.R . NO_OP.R . PipeOp.R . PipeOpBoxCox.R . PipeOpBranch.R . PipeOpChunk.R . PipeOpClassBalancing.R . PipeOpClassWeights.R . PipeOpClassifAvg.R . PipeOpColApply.R . PipeOpColRoles.R . PipeOpCollapseFactors.R . PipeOpCopy.R . PipeOpDateFeatures.R . PipeOpEncode.R . PipeOpEncodeImpact.R . PipeOpEncodeLmer.R . PipeOpEnsemble.R . PipeOpFeatureUnion.R . PipeOpFilter.R . PipeOpFixFactors.R . PipeOpHistBin.R . PipeOpICA.R . PipeOpImpute.R . PipeOpImputeConstant.R . PipeOpImputeHist.R . PipeOpImputeLearner.R . PipeOpImputeMean.R . PipeOpImputeMedian.R . PipeOpImputeMode.R . PipeOpImputeOOR.R . PipeOpImputeSample.R . PipeOpKernelPCA.R . PipeOpLearner.R . PipeOpLearnerCV.R . PipeOpMissingIndicators.R . PipeOpModelMatrix.R . PipeOpMultiplicity.R . PipeOpMutate.R . PipeOpNMF.R . PipeOpNOP.R . PipeOpOVR.R . PipeOpPCA.R . PipeOpProxy.R . PipeOpQuantileBin.R . PipeOpRandomProjection.R . PipeOpRandomResponse.R . PipeOpRegrAvg.R . PipeOpRemoveConstants.R . PipeOpRenameColumns.R . PipeOpScale.R . PipeOpScaleMaxAbs.R . PipeOpScaleRange.R . PipeOpSelect.R . PipeOpSmote.R . PipeOpSpatialSign.R . PipeOpSubsample.R . PipeOpTaskPreproc.R . PipeOpTextVectorizer.R . PipeOpThreshold.R . PipeOpTrafo.R . PipeOpTuneThreshold.R . PipeOpUnbranch.R . PipeOpVtreat.R . PipeOpYeoJohnson.R . Selector.R . assert_graph.R . bibentries.R . greplicate.R . gunion.R . mlr_graphs.R . mlr_pipeops.R . multiplicity.R . operators.R . pipeline_bagging.R . pipeline_branch.R . pipeline_greplicate.R . pipeline_ovr.R . pipeline_robustify.R . pipeline_stacking.R . pipeline_targettrafo.R . po.R . ppl.R . reexports.R . typecheck.R . utils.R . zzz.R .  Full mlr3pipelines package functions and examples
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