Package: mldr.resampling 0.2.3

Miguel Ángel Dávila

mldr.resampling: Resampling Algorithms for Multi-Label Datasets

Collection of the state of the art multi-label resampling algorithms. The objective of these algorithms is to achieve balance in multi-label datasets.

Authors:Miguel Ángel Dávila [cre], Francisco Charte [aut], María José Del Jesus [aut], Antonio Rivera [aut]

mldr.resampling_0.2.3.tar.gz
mldr.resampling_0.2.3.zip(r-4.7-any)mldr.resampling_0.2.3.zip(r-4.6-any)mldr.resampling_0.2.3.zip(r-4.5-any)
mldr.resampling_0.2.3.tgz(r-4.6-any)mldr.resampling_0.2.3.tgz(r-4.5-any)
mldr.resampling_0.2.3.tar.gz(r-4.7-any)mldr.resampling_0.2.3.tar.gz(r-4.6-any)
mldr.resampling_0.2.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mldr.resampling/json (API)

# Install 'mldr.resampling' in R:
install.packages('mldr.resampling', repos = c('https://madr0008.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/madr0008/mldr.resampling/issues

On CRAN:

Conda:

2.70 score 1 stars 7 scripts 267 downloads 1 mentions 15 exports 43 dependencies

Last updated from:93aa29ad60. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK120
source / vignettesOK197
linux-releaseOK109
macos-releaseOK120
macos-oldrelOK183
windows-develOK53
windows-releaseOK64
windows-oldrelOK63
wasm-releaseOK105

Exports:getNumCoresLPROSLPRUSMLeNNMLRkNNOSMLROSMLRUSMLSMOTEMLSOLMLTLMLULREMEDIALresamplesetNumCoressetParallel

Dependencies:base64encbslibcachemcirclizeclassclicolorspacecommonmarkdata.tabledigeste1071fastmapfontawesomefsGlobalOptionsgluehtmltoolshttpuvjquerylibjsonlitelaterlifecyclemagrittrmemoisemimemldrotelpbapplypracmapromisesproxyR6rappdirsRcpprlangsassshapeshinysourcetoolsvecsetswithrXMLxtable

Readme and manuals

Help Manual

Help pageTopics
Auxiliary function used by MLeNN. Computes the Hamming Distance between two instancesadjustedHammingDist
Auxiliary function used to calculate the distances between an instance and the ones with a specific active label. Euclidean distance is calculated for numeric attributes, and VDM for non numeric ones.calculateDistances
Auxiliary function used to calculate an auxiliary table to make VDM calculation fastercalculateTableVDM
Auxiliary function used by resample. It executes an algorithm, given as a string, and stores the resulting MLD in a arff fileexecuteAlgorithm
Auxiliary function used by MLSOL. Creates a synthetic sample based on two other samples, taking into account their typesgenerateInstanceMLSOL
Auxiliary function used by MLSOL and MLUL. Computes the kNN of every instance in a datasetgetAllNeighbors
Auxiliary function used by MLeNN and MLTL. Gets the kNN of every instance in a dataset, when compared to some of the restgetAllNeighbors2
Auxiliary function used by MLUL. For each instance in the dataset, given the neighbors structure, we compute its reverse nearest neighborsgetAllReverseNeighbors
Auxiliary function used by MLSOL and MLUL. For each instance in the dataset, we compute, for each label, the proportion of neighbors having an opposite class with respect to the proper instancegetC
Auxiliary function used to compute the neighbors of an instancegetNN
Get the number of cores available for parallel computinggetNumCores
Auxiliary function used by MLSOL and MLUL. For non outlier instances, it aggregates the values of C, taking into account the global class imbalancegetS
Auxiliary function used by MLUL. It computes the influence of each instance with respect to its reverse neighborsgetU
Auxiliary function used by MLUL. It calculates, for each instance, how important it is in the datasetgetV
Auxiliary function used by MLSOL and MLUL. For non outlier instances, it aggregates the values of S for each labelgetW
Auxiliary function used by MLSOL. Categorizes each pair instance-label of the dataset with a typeinitTypes
Randomly clones instances with minoritary labelsetsLPROS
Randomly deletes instances with majoritary labelsetsLPRUS
Multilabel edited Nearest Neighbor (MLeNN)MLeNN
Reverse-nearest neighborhood based oversampling for imbalanced, multi-label datasetsMLRkNNOS
Randomly clones instances with minoritary labelsMLROS
Randomly deletes instances with majoritary labelsMLRUS
Synthetic oversampling of multilabel instances (MLSMOTE)MLSMOTE
Multi-label oversampling based on local label imbalance (MLSOL)MLSOL
Multilabel approach for the Tomek Link undersampling algorithm (MLTL)MLTL
Multi-label undersampling based on local label imbalance (MLUL)MLUL
Auxiliary function used by MLSMOTE. Creates a synthetic sample based on values of attributes and labels of its neighborsnewSample
Decouples highly imbalanced labelsREMEDIAL
Interface function of the package. It executes one or several algorithms, given as strings, and stores the resulting MLDs in arff filesresample
Set the number of cores available for parallel computingsetNumCores
Enable/Disable parallel computingsetParallel
Auxiliary function used to calculate the Value Difference Metric (VDM) between two instances considering their non numeric attributesvdm