+.mlconfmat             Join two multi-label confusion matrix
[.mlresult              Filter a Multi-Label Result
as.bipartition          Convert a mlresult to a bipartition matrix
as.matrix.mlconfmat     Convert a multi-label Confusion Matrix to
                        matrix
as.matrix.mlresult      Convert a mlresult to matrix
as.mlresult             Convert a matrix prediction in a multi label
                        prediction
as.probability          Convert a mlresult to a probability matrix
as.ranking              Convert a mlresult to a ranking matrix
baseline                Baseline reference for multilabel
                        classification
br                      Binary Relevance for multi-label Classification
brplus                  BR+ or BRplus for multi-label Classification
cc                      Classifier Chains for multi-label
                        Classification
clr                     Calibrated Label Ranking (CLR) for multi-label
                        Classification
compute_multilabel_predictions
                        Compute the multi-label ensemble predictions
                        based on some vote schema
create_holdout_partition
                        Create a holdout partition based on the
                        specified algorithm
create_kfold_partition
                        Create the k-folds partition based on the
                        specified algorithm
create_random_subset    Create a random subset of a dataset
create_subset           Create a subset of a dataset
cv                      Multi-label cross-validation
dbr                     Dependent Binary Relevance (DBR) for
                        multi-label Classification
ebr                     Ensemble of Binary Relevance for multi-label
                        Classification
ecc                     Ensemble of Classifier Chains for multi-label
                        Classification
eps                     Ensemble of Pruned Set for multi-label
                        Classification
esl                     Ensemble of Single Label
fill_sparse_mldata      Fill sparse dataset with 0 or " values
fixed_threshold         Apply a fixed threshold in the results
foodtruck               Foodtruck multi-label dataset.
homer                   Hierarchy Of Multilabel classifiER (HOMER)
is.bipartition          Test if a mlresult contains crisp values as
                        default
is.probability          Test if a mlresult contains score values as
                        default
lcard_threshold         Threshold based on cardinality
lift                    LIFT for multi-label Classification
lp                      Label Powerset for multi-label Classification
mbr                     Meta-BR or 2BR for multi-label Classification
mcut_threshold          Maximum Cut Thresholding (MCut)
merge_mlconfmat         Join a list of multi-label confusion matrix
mldata                  Fix the mldr dataset to use factors
mlknn                   Multi-label KNN (ML-KNN) for multi-label
                        Classification
mlpredict               Prediction transformation problems
mltrain                 Build transformation models
multilabel_confusion_matrix
                        Compute the confusion matrix for a multi-label
                        prediction
multilabel_evaluate     Evaluate multi-label predictions
multilabel_measures     Return the name of all measures
multilabel_prediction   Create a mlresult object
normalize_mldata        Normalize numerical attributes
ns                      Nested Stacking for multi-label Classification
partition_fold          Create the multi-label dataset from folds
pcut_threshold          Proportional Thresholding (PCut)
ppt                     Pruned Problem Transformation for multi-label
                        Classification
predict.BASELINEmodel   Predict Method for BASELINE
predict.BRPmodel        Predict Method for BR+ (brplus)
predict.BRmodel         Predict Method for Binary Relevance
predict.CCmodel         Predict Method for Classifier Chains
predict.CLRmodel        Predict Method for CLR
predict.DBRmodel        Predict Method for DBR
predict.EBRmodel        Predict Method for Ensemble of Binary Relevance
predict.ECCmodel        Predict Method for Ensemble of Classifier
                        Chains
predict.EPSmodel        Predict Method for Ensemble of Pruned Set
                        Transformation
predict.ESLmodel        Predict Method for Ensemble of Single Label
predict.HOMERmodel      Predict Method for HOMER
predict.LIFTmodel       Predict Method for LIFT
predict.LPmodel         Predict Method for Label Powerset
predict.MBRmodel        Predict Method for Meta-BR/2BR
predict.MLKNNmodel      Predict Method for ML-KNN
predict.NSmodel         Predict Method for Nested Stacking
predict.PPTmodel        Predict Method for Pruned Problem
                        Transformation
predict.PSmodel         Predict Method for Pruned Set Transformation
predict.PruDentmodel    Predict Method for PruDent
predict.RAkELmodel      Predict Method for RAkEL
predict.RDBRmodel       Predict Method for RDBR
predict.RPCmodel        Predict Method for RPC
print.BRPmodel          Print BRP model
print.BRmodel           Print BR model
print.CCmodel           Print CC model
print.CLRmodel          Print CLR model
print.DBRmodel          Print DBR model
print.EBRmodel          Print EBR model
print.ECCmodel          Print ECC model
print.EPSmodel          Print EPS model
print.ESLmodel          Print ESL model
print.LIFTmodel         Print LIFT model
print.LPmodel           Print LP model
print.MBRmodel          Print MBR model
print.MLKNNmodel        Print MLKNN model
print.NSmodel           Print NS model
print.PPTmodel          Print PPT model
print.PSmodel           Print PS model
print.PruDentmodel      Print PruDent model
print.RAkELmodel        Print RAkEL model
print.RDBRmodel         Print RDBR model
print.RPCmodel          Print RPC model
print.kFoldPartition    Print a kFoldPartition object
print.majorityModel     Print Majority model
print.mlconfmat         Print a Multi-label Confusion Matrix
print.mlresult          Print the mlresult
print.randomModel       Print Random model
prudent                 PruDent classifier for multi-label
                        Classification
ps                      Pruned Set for multi-label Classification
rakel                   Random k-labelsets for multilabel
                        classification
rcut_threshold          Rank Cut (RCut) threshold method
rdbr                    Recursive Dependent Binary Relevance (RDBR) for
                        multi-label Classification
remove_attributes       Remove attributes from the dataset
remove_labels           Remove labels from the dataset
remove_skewness_labels
                        Remove unusual or very common labels
remove_unique_attributes
                        Remove unique attributes
remove_unlabeled_instances
                        Remove examples without labels
replace_nominal_attributes
                        Replace nominal attributes Replace the nominal
                        attributes by binary attributes.
rpc                     Ranking by Pairwise Comparison (RPC) for
                        multi-label Classification
scut_threshold          SCut Score-based method
subset_correction       Subset Correction of a predicted result
summary.mltransformation
                        Summary method for mltransformation
toyml                   Toy multi-label dataset.
utiml                   utiml: Utilities for Multi-Label Learning
utiml_measure_names     Return the name of measures
