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      "date": "2025-08-01"
    },
    {
      "version": "0.10.0",
      "date": "2025-11-07"
    },
    {
      "version": "0.11.0",
      "date": "2026-03-01"
    }
  ],
  "_exports": [
    "%>>!%",
    "%>>%",
    "%among%",
    "add_class_hierarchy_cache",
    "as_graph",
    "as_pipeop",
    "as.CnfAtom",
    "as.CnfClause",
    "as.CnfFormula",
    "as.data.table",
    "as.Multiplicity",
    "assert_graph",
    "assert_pipeop",
    "chain_graphs",
    "CnfAtom",
    "CnfClause",
    "CnfFormula",
    "CnfSymbol",
    "CnfUniverse",
    "concat_graphs",
    "filter_noop",
    "FilterEnsemble",
    "Graph",
    "GraphLearner",
    "greplicate",
    "gunion",
    "is_noop",
    "is.Multiplicity",
    "LearnerClassifAvg",
    "LearnerRegrAvg",
    "mlr_graphs",
    "mlr_pipeops",
    "Multiplicity",
    "NO_OP",
    "pipeline_bagging",
    "pipeline_branch",
    "pipeline_convert_types",
    "pipeline_greplicate",
    "pipeline_ovr",
    "pipeline_robustify",
    "pipeline_stacking",
    "pipeline_targettrafo",
    "PipeOp",
    "PipeOpADAS",
    "PipeOpBLSmote",
    "PipeOpBoxCox",
    "PipeOpBranch",
    "PipeOpChunk",
    "PipeOpClassBalancing",
    "PipeOpClassifAvg",
    "PipeOpClassWeights",
    "PipeOpClassWeightsEx",
    "PipeOpColApply",
    "PipeOpCollapseFactors",
    "PipeOpColRoles",
    "PipeOpCopy",
    "PipeOpDateFeatures",
    "PipeOpDecode",
    "PipeOpEncode",
    "PipeOpEncodeImpact",
    "PipeOpEncodeLmer",
    "PipeOpEncodePL",
    "PipeOpEncodePLQuantiles",
    "PipeOpEncodePLTree",
    "PipeOpEnsemble",
    "PipeOpFeatureUnion",
    "PipeOpFilter",
    "PipeOpFixFactors",
    "PipeOpHistBin",
    "PipeOpICA",
    "PipeOpImpute",
    "PipeOpImputeConstant",
    "PipeOpImputeHist",
    "PipeOpImputeLearner",
    "PipeOpImputeMean",
    "PipeOpImputeMedian",
    "PipeOpImputeMode",
    "PipeOpImputeOOR",
    "PipeOpImputeSample",
    "PipeOpInfo",
    "PipeOpIsomap",
    "PipeOpKernelPCA",
    "PipeOpLearner",
    "PipeOpLearnerCV",
    "PipeOpLearnerPICVPlus",
    "PipeOpLearnerQuantiles",
    "PipeOpMissInd",
    "PipeOpModelMatrix",
    "PipeOpMultiplicityExply",
    "PipeOpMultiplicityImply",
    "PipeOpMutate",
    "PipeOpNearmiss",
    "PipeOpNMF",
    "PipeOpNOP",
    "PipeOpOVRSplit",
    "PipeOpOVRUnite",
    "PipeOpPCA",
    "PipeOpProxy",
    "PipeOpQuantileBin",
    "PipeOpRandomProjection",
    "PipeOpRandomResponse",
    "PipeOpRegrAvg",
    "PipeOpRemoveConstants",
    "PipeOpRenameColumns",
    "PipeOpReplicate",
    "PipeOpRowApply",
    "PipeOpScale",
    "PipeOpScaleMaxAbs",
    "PipeOpScaleRange",
    "PipeOpSelect",
    "PipeOpSmote",
    "PipeOpSmoteNC",
    "PipeOpSpatialSign",
    "PipeOpSplines",
    "PipeOpSubsample",
    "PipeOpTargetInvert",
    "PipeOpTargetMutate",
    "PipeOpTargetTrafo",
    "PipeOpTargetTrafoScaleRange",
    "PipeOpTaskPreproc",
    "PipeOpTaskPreprocSimple",
    "PipeOpTextVectorizer",
    "PipeOpThreshold",
    "PipeOpTomek",
    "PipeOpTuneThreshold",
    "PipeOpUnbranch",
    "PipeOpVtreat",
    "PipeOpYeoJohnson",
    "po",
    "pos",
    "ppl",
    "ppls",
    "preproc",
    "register_autoconvert_function",
    "reset_autoconvert_register",
    "reset_class_hierarchy_cache",
    "selector_all",
    "selector_cardinality_greater_than",
    "selector_grep",
    "selector_intersect",
    "selector_invert",
    "selector_missing",
    "selector_name",
    "selector_none",
    "selector_setdiff",
    "selector_type",
    "selector_union"
  ],
  "_help": [
    {
      "page": "mlr3pipelines-package",
      "title": "mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'",
      "topics": [
        "mlr3pipelines-package",
        "mlr3pipelines"
      ]
    },
    {
      "page": "grapes-greater-than-greater-than-grapes",
      "title": "PipeOp Composition Operator",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "%>>!%",
        "%>>%",
        "concat_graphs"
      ]
    },
    {
      "page": "add_class_hierarchy_cache",
      "title": "Add a Class Hierarchy to the Cache",
      "concept": [
        "class hierarchy operations"
      ],
      "topics": [
        "add_class_hierarchy_cache"
      ]
    },
    {
      "page": "as_graph",
      "title": "Conversion to mlr3pipelines Graph",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "as_graph"
      ]
    },
    {
      "page": "as_pipeop",
      "title": "Conversion to mlr3pipelines PipeOp",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "as_pipeop"
      ]
    },
    {
      "page": "as.Multiplicity",
      "title": "Convert an object to a Multiplicity",
      "topics": [
        "as.Multiplicity"
      ]
    },
    {
      "page": "assert_graph",
      "title": "Assertion for mlr3pipelines Graph",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "assert_graph"
      ]
    },
    {
      "page": "assert_pipeop",
      "title": "Assertion for mlr3pipelines PipeOp",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "assert_pipeop"
      ]
    },
    {
      "page": "chain_graphs",
      "title": "Chain a Series of Graphs",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "chain_graphs"
      ]
    },
    {
      "page": "filter_noop",
      "title": "Remove NO_OPs from a List",
      "concept": [
        "Path Branching"
      ],
      "topics": [
        "filter_noop"
      ]
    },
    {
      "page": "Graph",
      "title": "Graph Base Class",
      "concept": [
        "mlr3pipelines backend related"
      ],
      "topics": [
        "Graph"
      ]
    },
    {
      "page": "greplicate",
      "title": "Create Disjoint Graph Union of Copies of a Graph",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "greplicate"
      ]
    },
    {
      "page": "gunion",
      "title": "Disjoint Union of Graphs",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "gunion"
      ]
    },
    {
      "page": "is_noop",
      "title": "Test for NO_OP",
      "concept": [
        "Path Branching"
      ],
      "topics": [
        "is_noop"
      ]
    },
    {
      "page": "is.Multiplicity",
      "title": "Check if an object is a Multiplicity",
      "topics": [
        "is.Multiplicity"
      ]
    },
    {
      "page": "mlr_filters_ensemble",
      "title": "Filter Ensemble",
      "topics": [
        "FilterEnsemble",
        "mlr_filters_ensemble"
      ]
    },
    {
      "page": "mlr_graphs",
      "title": "Dictionary of (sub-)graphs",
      "concept": [
        "Dictionaries",
        "mlr3pipelines backend related"
      ],
      "topics": [
        "mlr_graphs"
      ]
    },
    {
      "page": "mlr_graphs_bagging",
      "title": "Create a bagging learner",
      "topics": [
        "mlr_graphs_bagging",
        "pipeline_bagging"
      ]
    },
    {
      "page": "mlr_graphs_branch",
      "title": "Branch Between Alternative Paths",
      "topics": [
        "mlr_graphs_branch",
        "pipeline_branch"
      ]
    },
    {
      "page": "mlr_graphs_convert_types",
      "title": "Convert Column Types",
      "topics": [
        "mlr_graphs_convert_types",
        "pipeline_convert_types"
      ]
    },
    {
      "page": "mlr_graphs_greplicate",
      "title": "Create Disjoint Graph Union of Copies of a Graph",
      "concept": [
        "Graph operators"
      ],
      "topics": [
        "mlr_graphs_greplicate",
        "pipeline_greplicate"
      ]
    },
    {
      "page": "mlr_graphs_ovr",
      "title": "Create A Graph to Perform \"One vs. Rest\" classification.",
      "topics": [
        "mlr_graphs_ovr",
        "pipeline_ovr"
      ]
    },
    {
      "page": "mlr_graphs_robustify",
      "title": "Robustify a learner",
      "topics": [
        "mlr_graphs_robustify",
        "pipeline_robustify"
      ]
    },
    {
      "page": "mlr_graphs_stacking",
      "title": "Create A Graph to Perform Stacking.",
      "topics": [
        "mlr_graphs_stacking",
        "pipeline_stacking"
      ]
    },
    {
      "page": "mlr_graphs_targettrafo",
      "title": "Transform and Re-Transform the Target Variable",
      "topics": [
        "mlr_graphs_targettrafo",
        "pipeline_targettrafo"
      ]
    },
    {
      "page": "mlr_learners_avg",
      "title": "Optimized Weighted Average of Features for Classification and Regression",
      "concept": [
        "Ensembles",
        "Learners"
      ],
      "topics": [
        "LearnerClassifAvg",
        "LearnerRegrAvg",
        "mlr_learners_avg",
        "mlr_learners_classif.avg",
        "mlr_learners_regr.avg"
      ]
    },
    {
      "page": "mlr_learners_graph",
      "title": "Encapsulate a Graph as a Learner",
      "concept": [
        "Learners"
      ],
      "topics": [
        "GraphLearner",
        "mlr_learners_graph"
      ]
    },
    {
      "page": "mlr_pipeops",
      "title": "Dictionary of PipeOps",
      "concept": [
        "Dictionaries",
        "PipeOps",
        "mlr3pipelines backend related"
      ],
      "topics": [
        "mlr_pipeops"
      ]
    },
    {
      "page": "mlr_pipeops_adas",
      "title": "ADAS Balancing",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_adas",
        "PipeOpADAS"
      ]
    },
    {
      "page": "mlr_pipeops_blsmote",
      "title": "BLSMOTE Balancing",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_blsmote",
        "PipeOpBLSmote"
      ]
    },
    {
      "page": "mlr_pipeops_boxcox",
      "title": "Box-Cox Transformation of Numeric Features",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_boxcox",
        "PipeOpBoxCox"
      ]
    },
    {
      "page": "mlr_pipeops_branch",
      "title": "Path Branching",
      "concept": [
        "Path Branching",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_branch",
        "PipeOpBranch"
      ]
    },
    {
      "page": "mlr_pipeops_chunk",
      "title": "Chunk Input into Multiple Outputs",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_chunk",
        "PipeOpChunk"
      ]
    },
    {
      "page": "mlr_pipeops_classbalancing",
      "title": "Class Balancing",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_classbalancing",
        "PipeOpClassBalancing"
      ]
    },
    {
      "page": "mlr_pipeops_classifavg",
      "title": "Majority Vote Prediction",
      "concept": [
        "Ensembles",
        "Multiplicity PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_classifavg",
        "PipeOpClassifAvg"
      ]
    },
    {
      "page": "mlr_pipeops_classweights",
      "title": "Class Weights for Sample Weighting",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_classweights",
        "PipeOpClassWeights"
      ]
    },
    {
      "page": "mlr_pipeops_classweightsex",
      "title": "Class Weights for Sample Weighting - Extended",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_classweightsex",
        "PipeOpClassWeightsEx"
      ]
    },
    {
      "page": "mlr_pipeops_colapply",
      "title": "Apply a Function to each Column of a Task",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_colapply",
        "PipeOpColApply"
      ]
    },
    {
      "page": "mlr_pipeops_collapsefactors",
      "title": "Collapse Factors",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_collapsefactors",
        "PipeOpCollapseFactors"
      ]
    },
    {
      "page": "mlr_pipeops_colroles",
      "title": "Change Column Roles of a Task",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_colroles",
        "PipeOpColRoles"
      ]
    },
    {
      "page": "mlr_pipeops_copy",
      "title": "Copy Input Multiple Times",
      "concept": [
        "PipeOps",
        "Placeholder Pipeops"
      ],
      "topics": [
        "mlr_pipeops_copy",
        "PipeOpCopy"
      ]
    },
    {
      "page": "mlr_pipeops_datefeatures",
      "title": "Preprocess Date Features",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_datefeatures",
        "PipeOpDateFeatures"
      ]
    },
    {
      "page": "mlr_pipeops_decode",
      "title": "Reverse Factor Encoding",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_decode",
        "PipeOpDecode"
      ]
    },
    {
      "page": "mlr_pipeops_encode",
      "title": "Factor Encoding",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_encode",
        "PipeOpEncode"
      ]
    },
    {
      "page": "mlr_pipeops_encodeimpact",
      "title": "Conditional Target Value Impact Encoding",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_encodeimpact",
        "PipeOpEncodeImpact"
      ]
    },
    {
      "page": "mlr_pipeops_encodelmer",
      "title": "Impact Encoding with Random Intercept Models",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_encodelmer",
        "PipeOpEncodeLmer"
      ]
    },
    {
      "page": "mlr_pipeops_encodeplquantiles",
      "title": "Piecewise Linear Encoding using Quantiles",
      "concept": [
        "Piecewise Linear Encoding PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_encodeplquantiles",
        "PipeOpEncodePLQuantiles"
      ]
    },
    {
      "page": "mlr_pipeops_encodepltree",
      "title": "Piecewise Linear Encoding using Decision Trees",
      "concept": [
        "Piecewise Linear Encoding PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_encodepltree",
        "PipeOpEncodePLTree"
      ]
    },
    {
      "page": "mlr_pipeops_featureunion",
      "title": "Aggregate Features from Multiple Inputs",
      "concept": [
        "Multiplicity PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_featureunion",
        "PipeOpFeatureUnion"
      ]
    },
    {
      "page": "mlr_pipeops_filter",
      "title": "Feature Filtering",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_filter",
        "PipeOpFilter"
      ]
    },
    {
      "page": "mlr_pipeops_fixfactors",
      "title": "Fix Factor Levels",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_fixfactors",
        "PipeOpFixFactors"
      ]
    },
    {
      "page": "mlr_pipeops_histbin",
      "title": "Split Numeric Features into Equally Spaced Bins",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_histbin",
        "PipeOpHistBin"
      ]
    },
    {
      "page": "mlr_pipeops_ica",
      "title": "Independent Component Analysis",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_ica",
        "PipeOpICA"
      ]
    },
    {
      "page": "mlr_pipeops_imputeconstant",
      "title": "Impute Features by a Constant",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputeconstant",
        "PipeOpImputeConstant"
      ]
    },
    {
      "page": "mlr_pipeops_imputehist",
      "title": "Impute Numeric, Integer, POSIXct or Date Features by Histogram",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputehist",
        "PipeOpImputeHist"
      ]
    },
    {
      "page": "mlr_pipeops_imputelearner",
      "title": "Impute Features by Fitting a Learner",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputelearner",
        "PipeOpImputeLearner"
      ]
    },
    {
      "page": "mlr_pipeops_imputemean",
      "title": "Impute Numeric, Integer, POSIXct or Date Features by their Mean",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputemean",
        "PipeOpImputeMean"
      ]
    },
    {
      "page": "mlr_pipeops_imputemedian",
      "title": "Impute Numeric, Integer, POSIXct or Date Features by their Median",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputemedian",
        "PipeOpImputeMedian"
      ]
    },
    {
      "page": "mlr_pipeops_imputemode",
      "title": "Impute Features by their Mode",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputemode",
        "PipeOpImputeMode"
      ]
    },
    {
      "page": "mlr_pipeops_imputeoor",
      "title": "Out of Range Imputation",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputeoor",
        "PipeOpImputeOOR"
      ]
    },
    {
      "page": "mlr_pipeops_imputesample",
      "title": "Impute Features by Sampling",
      "concept": [
        "Imputation PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_imputesample",
        "PipeOpImputeSample"
      ]
    },
    {
      "page": "mlr_pipeops_info",
      "title": "Customizable Information Printer",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_info",
        "PipeOpInfo"
      ]
    },
    {
      "page": "mlr_pipeops_isomap",
      "title": "Algorithm for Dimensionality Reduction",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_isomap",
        "PipeOpIsomap"
      ]
    },
    {
      "page": "mlr_pipeops_kernelpca",
      "title": "Kernelized Principal Component Analysis",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_kernelpca",
        "PipeOpKernelPCA"
      ]
    },
    {
      "page": "mlr_pipeops_learner",
      "title": "Wrap a Learner into a PipeOp",
      "concept": [
        "Meta PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_learner",
        "PipeOpLearner"
      ]
    },
    {
      "page": "mlr_pipeops_learner_cv",
      "title": "Wrap a Learner into a PipeOp with Cross-validated Predictions as Features",
      "concept": [
        "Meta PipeOps",
        "Pipeops"
      ],
      "topics": [
        "mlr_pipeops_learner_cv",
        "PipeOpLearnerCV"
      ]
    },
    {
      "page": "mlr_pipeops_learner_pi_cvplus",
      "title": "Wrap a Learner into a PipeOp with Cross-validation Plus Confidence Intervals as Predictions",
      "concept": [
        "Meta PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_learner_pi_cvplus",
        "PipeOpLearnerPICVPlus"
      ]
    },
    {
      "page": "mlr_pipeops_learner_quantiles",
      "title": "Wrap a Learner into a PipeOp to predict multiple Quantiles",
      "concept": [
        "Meta PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_learner_quantiles",
        "PipeOpLearnerQuantiles"
      ]
    },
    {
      "page": "mlr_pipeops_missind",
      "title": "Add Missing Indicator Columns",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_missind",
        "PipeOpMissInd"
      ]
    },
    {
      "page": "mlr_pipeops_modelmatrix",
      "title": "Transform Columns by Constructing a Model Matrix",
      "concept": [
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_modelmatrix",
        "PipeOpModelMatrix"
      ]
    },
    {
      "page": "mlr_pipeops_multiplicityexply",
      "title": "Explicate a Multiplicity",
      "concept": [
        "Experimental Features",
        "Multiplicity PipeOps",
        "PipeOps"
      ],
      "topics": [
        "mlr_pipeops_multiplicityexply",
        "PipeOpMultiplicityExply"
      ]
    },
    {
      "page": "mlr_pipeops_multiplicityimply",
      "title": "Implicate a Multiplicity",
      "concept": [
        "Experimental Features",
        "Multiplicity PipeOps",
        "PipeOps"
      ],
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