Multi-label learning methods and others utilities to support multi- label classification in R.

Documentation

Manual: utiml.pdf
Vignette: utiml: Utilities for Multi-label Learning

Maintainer: Adriano Rivolli <rivolli at utfpr.edu.br>

Author(s): Adriano Rivolli*

Install package and any missing dependencies by running this line in your R console:

install.packages("utiml")

Depends R (>= 3.0.0), mldr(>=0.3.22)
Imports stats, utils
Suggests C50, e1071, FSelector, infotheo, kknn, knitr, parallel, randomForest, rJava(>=0.9), rmarkdown, rpart, RWeka(>=0.4), testthat, xgboost
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Package utiml
Materials
URL https://github.com/rivolli/utiml
Task Views
Version 0.1.1
Published 2016-11-19
License GPL | file LICENSE
BugReports https://github.com/rivolli/utiml
SystemRequirements
NeedsCompilation no
Citation
CRAN checks utiml check results
Package source utiml_0.1.1.tar.gz