Preprocessing Operators and Pipelines for 'mlr3'

add_class_hierarchy_cache | Add a Class Hierarchy to the Cache |

as_graph | Conversion to mlr3pipelines Graph |

as.Multiplicity | Convert an object to a Multiplicity |

as_pipeop | Conversion to mlr3pipelines PipeOp |

assert_graph | Assertion for mlr3pipelines Graph |

assert_pipeop | Assertion for mlr3pipelines PipeOp |

chain_graphs | Chain a Series of Graphs |

filter_noop | Remove NO_OPs from a List |

grapes-greater-than-greater-than-grapes | PipeOp Composition Operator |

Graph | Graph Base Class |

greplicate | Create Disjoint Graph Union of Copies of a Graph |

gunion | Disjoint Union of Graphs |

is.Multiplicity | Check if an object is a Multiplicity |

is_noop | Test for NO_OP |

mlr3pipelines-package | mlr3pipelines: Preprocessing Operators and Pipelines for... |

mlr_graphs | Dictionary of (sub-)graphs |

mlr_graphs_bagging | Create a bagging learner |

mlr_graphs_branch | Branch Between Alternative Paths |

mlr_graphs_greplicate | Create Disjoint Graph Union of Copies of a Graph |

mlr_graphs_ovr | Create A Graph to Perform "One vs. Rest" classification. |

mlr_graphs_robustify | Robustify a learner |

mlr_graphs_stacking | Create A Graph to Perform Stacking. |

mlr_graphs_targettrafo | Transform and Re-Transform the Target Variable |

mlr_learners_avg | Optimized Weighted Average of Features for Classification and... |

mlr_learners_graph | Encapsulate a Graph as a Learner |

mlr_pipeops | Dictionary of PipeOps |

mlr_pipeops_boxcox | Box-Cox Transformation of Numeric Features |

mlr_pipeops_branch | Path Branching |

mlr_pipeops_chunk | Chunk Input into Multiple Outputs |

mlr_pipeops_classbalancing | Class Balancing |

mlr_pipeops_classifavg | Majority Vote Prediction |

mlr_pipeops_classweights | Class Weights for Sample Weighting |

mlr_pipeops_colapply | Apply a Function to each Column of a Task |

mlr_pipeops_collapsefactors | Collapse Factors |

mlr_pipeops_colroles | Change Column Roles of a Task |

mlr_pipeops_copy | Copy Input Multiple Times |

mlr_pipeops_datefeatures | Preprocess Date Features |

mlr_pipeops_encode | Factor Encoding |

mlr_pipeops_encodeimpact | Conditional Target Value Impact Encoding |

mlr_pipeops_encodelmer | Impact Encoding with Random Intercept Models |

mlr_pipeops_featureunion | Aggregate Features from Multiple Inputs |

mlr_pipeops_filter | Feature Filtering |

mlr_pipeops_fixfactors | Fix Factor Levels |

mlr_pipeops_histbin | Split Numeric Features into Equally Spaced Bins |

mlr_pipeops_ica | Independent Component Analysis |

mlr_pipeops_imputeconstant | Impute Features by a Constant |

mlr_pipeops_imputehist | Impute Numerical Features by Histogram |

mlr_pipeops_imputelearner | Impute Features by Fitting a Learner |

mlr_pipeops_imputemean | Impute Numerical Features by their Mean |

mlr_pipeops_imputemedian | Impute Numerical Features by their Median |

mlr_pipeops_imputemode | Impute Features by their Mode |

mlr_pipeops_imputeoor | Out of Range Imputation |

mlr_pipeops_imputesample | Impute Features by Sampling |

mlr_pipeops_kernelpca | Kernelized Principle Component Analysis |

mlr_pipeops_learner | Wrap a Learner into a PipeOp |

mlr_pipeops_learner_cv | Wrap a Learner into a PipeOp with Cross-validated Predictions... |

mlr_pipeops_missind | Add Missing Indicator Columns |

mlr_pipeops_modelmatrix | Transform Columns by Constructing a Model Matrix |

mlr_pipeops_multiplicityexply | Explicate a Multiplicity |

mlr_pipeops_multiplicityimply | Implicate a Multiplicity |

mlr_pipeops_mutate | Add Features According to Expressions |

mlr_pipeops_nmf | Non-negative Matrix Factorization |

mlr_pipeops_nop | Simply Push Input Forward |

mlr_pipeops_ovrsplit | Split a Classification Task into Binary Classification Tasks |

mlr_pipeops_ovrunite | Unite Binary Classification Tasks |

mlr_pipeops_pca | Principle Component Analysis |

mlr_pipeops_proxy | Wrap another PipeOp or Graph as a Hyperparameter |

mlr_pipeops_quantilebin | Split Numeric Features into Quantile Bins |

mlr_pipeops_randomprojection | Project Numeric Features onto a Randomly Sampled Subspace |

mlr_pipeops_randomresponse | Generate a Randomized Response Prediction |

mlr_pipeops_regravg | Weighted Prediction Averaging |

mlr_pipeops_removeconstants | Remove Constant Features |

mlr_pipeops_renamecolumns | Rename Columns |

mlr_pipeops_replicate | Replicate the Input as a Multiplicity |

mlr_pipeops_scale | Center and Scale Numeric Features |

mlr_pipeops_scalemaxabs | Scale Numeric Features with Respect to their Maximum Absolute... |

mlr_pipeops_scalerange | Linearly Transform Numeric Features to Match Given Boundaries |

mlr_pipeops_select | Remove Features Depending on a Selector |

mlr_pipeops_smote | SMOTE Balancing |

mlr_pipeops_spatialsign | Normalize Data Row-wise |

mlr_pipeops_subsample | Subsampling |

mlr_pipeops_targetinvert | Invert Target Transformations |

mlr_pipeops_targetmutate | Transform a Target by a Function |

mlr_pipeops_targettrafoscalerange | Linearly Transform a Numeric Target to Match Given Boundaries |

mlr_pipeops_textvectorizer | Bag-of-word Representation of Character Features |

mlr_pipeops_threshold | Change the Threshold of a Classification Prediction |

mlr_pipeops_tunethreshold | Tune the Threshold of a Classification Prediction |

mlr_pipeops_unbranch | Unbranch Different Paths |

mlr_pipeops_updatetarget | Transform a Target without an Explicit Inversion |

mlr_pipeops_vtreat | Interface to the vtreat Package |

mlr_pipeops_yeojohnson | Yeo-Johnson Transformation of Numeric Features |

Multiplicity | Multiplicity |

NO_OP | No-Op Sentinel Used for Alternative Branching |

PipeOp | PipeOp Base Class |

PipeOpEnsemble | Ensembling Base Class |

PipeOpImpute | Imputation Base Class |

PipeOpTargetTrafo | Target Transformation Base Class |

PipeOpTaskPreproc | Task Preprocessing Base Class |

PipeOpTaskPreprocSimple | Simple Task Preprocessing Base Class |

po | Shorthand PipeOp Constructor |

ppl | Shorthand Graph Constructor |

reexports | Objects exported from other packages |

register_autoconvert_function | Add Autoconvert Function to Conversion Register |

reset_autoconvert_register | Reset Autoconvert Register |

reset_class_hierarchy_cache | Reset the Class Hierarchy Cache |

Selector | Selector Functions |

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