Man pages for utiml
Utilities for Multi-Label Learning

as.bipartitionConvert a mlresult to a bipartition matrix
as.matrix.mlconfmatConvert a multi-label Confusion Matrix to matrix
as.matrix.mlresultConvert a mlresult to matrix
as.mlresultConvert a matrix prediction in a multi label prediction
as.probabilityConvert a mlresult to a probability matrix
as.rankingConvert a mlresult to a ranking matrix
baselineBaseline reference for multilabel classification
brBinary Relevance for multi-label Classification
brplusBR+ or BRplus for multi-label Classification
ccClassifier Chains for multi-label Classification
clrCalibrated Label Ranking (CLR) for multi-label Classification
compute_multilabel_predictionsCompute the multi-label ensemble predictions based on some...
create_holdout_partitionCreate a holdout partition based on the specified algorithm
create_kfold_partitionCreate the k-folds partition based on the specified algorithm
create_random_subsetCreate a random subset of a dataset
create_subsetCreate a subset of a dataset
ctrlCTRL model for multi-label Classification
cvMulti-label cross-validation
dbrDependent Binary Relevance (DBR) for multi-label...
ebrEnsemble of Binary Relevance for multi-label Classification
eccEnsemble of Classifier Chains for multi-label Classification
epsEnsemble of Pruned Set for multi-label Classification
eslEnsemble of Single Label
fill_sparse_mldataFill sparse dataset with 0 or " values
fixed_thresholdApply a fixed threshold in the results
foodtruckFoodtruck multi-label dataset.
homerHierarchy Of Multilabel classifiER (HOMER)
is.bipartitionTest if a mlresult contains crisp values as default
is.probabilityTest if a mlresult contains score values as default
lcard_thresholdThreshold based on cardinality
liftLIFT for multi-label Classification
lpLabel Powerset for multi-label Classification
mbrMeta-BR or 2BR for multi-label Classification
mcut_thresholdMaximum Cut Thresholding (MCut)
merge_mlconfmatJoin a list of multi-label confusion matrix
mldataFix the mldr dataset to use factors
mlknnMulti-label KNN (ML-KNN) for multi-label Classification
mlpredictPrediction transformation problems
mltrainBuild transformation models
multilabel_confusion_matrixCompute the confusion matrix for a multi-label prediction
multilabel_evaluateEvaluate multi-label predictions
multilabel_measuresReturn the name of all measures
multilabel_predictionCreate a mlresult object
normalize_mldataNormalize numerical attributes
nsNested Stacking for multi-label Classification
partition_foldCreate the multi-label dataset from folds
pcut_thresholdProportional Thresholding (PCut)
plus-.mlconfmatJoin two multi-label confusion matrix
pptPruned Problem Transformation for multi-label Classification
predict.BASELINEmodelPredict Method for BASELINE
predict.BRmodelPredict Method for Binary Relevance
predict.BRPmodelPredict Method for BR+ (brplus)
predict.CCmodelPredict Method for Classifier Chains
predict.CLRmodelPredict Method for CLR
predict.CTRLmodelPredict Method for CTRL
predict.DBRmodelPredict Method for DBR
predict.EBRmodelPredict Method for Ensemble of Binary Relevance
predict.ECCmodelPredict Method for Ensemble of Classifier Chains
predict.EPSmodelPredict Method for Ensemble of Pruned Set Transformation
predict.ESLmodelPredict Method for Ensemble of Single Label
predict.HOMERmodelPredict Method for HOMER
predict.LIFTmodelPredict Method for LIFT
predict.LPmodelPredict Method for Label Powerset
predict.MBRmodelPredict Method for Meta-BR/2BR
predict.MLKNNmodelPredict Method for ML-KNN
predict.NSmodelPredict Method for Nested Stacking
predict.PPTmodelPredict Method for Pruned Problem Transformation
predict.PruDentmodelPredict Method for PruDent
predict.PSmodelPredict Method for Pruned Set Transformation
predict.RAkELmodelPredict Method for RAkEL
predict.RDBRmodelPredict Method for RDBR
predict.RPCmodelPredict Method for RPC
print.BRmodelPrint BR model
print.BRPmodelPrint BRP model
print.CCmodelPrint CC model
print.CLRmodelPrint CLR model
print.CTRLmodelPrint CTRL model
print.DBRmodelPrint DBR model
print.EBRmodelPrint EBR model
print.ECCmodelPrint ECC model
print.EPSmodelPrint EPS model
print.ESLmodelPrint ESL model
print.kFoldPartitionPrint a kFoldPartition object
print.LIFTmodelPrint LIFT model
print.LPmodelPrint LP model
print.majorityModelPrint Majority model
print.MBRmodelPrint MBR model
print.mlconfmatPrint a Multi-label Confusion Matrix
print.MLKNNmodelPrint MLKNN model
print.mlresultPrint the mlresult
print.NSmodelPrint NS model
print.PPTmodelPrint PPT model
print.PruDentmodelPrint PruDent model
print.PSmodelPrint PS model
print.RAkELmodelPrint RAkEL model
print.randomModelPrint Random model
print.RDBRmodelPrint RDBR model
print.RPCmodelPrint RPC model
prudentPruDent classifier for multi-label Classification
psPruned Set for multi-label Classification
rakelRandom k-labelsets for multilabel classification
rcut_thresholdRank Cut (RCut) threshold method
rdbrRecursive Dependent Binary Relevance (RDBR) for multi-label...
remove_attributesRemove attributes from the dataset
remove_labelsRemove labels from the dataset
remove_skewness_labelsRemove unusual or very common labels
remove_unique_attributesRemove unique attributes
remove_unlabeled_instancesRemove examples without labels
replace_nominal_attributesReplace nominal attributes Replace the nominal attributes by...
rpcRanking by Pairwise Comparison (RPC) for multi-label...
scut_thresholdSCut Score-based method
sub-.mlresultFilter a Multi-Label Result
subset_correctionSubset Correction of a predicted result
summary.mltransformationSummary method for mltransformation
toymlToy multi-label dataset.
utimlutiml: Utilities for Multi-Label Learning
utiml documentation built on April 20, 2018, 1:04 a.m.