Package: utiml
Type: Package
Title: Utilities for Multi-Label Learning
Version: 0.1.6
Date: 2020-02-06
Authors@R: person("Adriano", "Rivolli", email = "rivolli@utfpr.edu.br",
                  role = c("aut", "cre"))
Description: Multi-label learning strategies and others procedures to support multi-
  label classification in R. The package provides a set of multi-label procedures such as
  sampling methods, transformation strategies, threshold functions, pre-processing 
  techniques and evaluation metrics. A complete overview of the matter can be seen in
  Zhang, M. and Zhou, Z. (2014) <doi:10.1109/TKDE.2013.39> and Gibaja, E. and 
  Ventura, S. (2015) A Tutorial on Multi-label Learning.
URL: https://github.com/rivolli/utiml
Depends: R (>= 3.0.0), mldr(>= 0.4.0), parallel, ROCR
Imports: stats, utils, methods
Suggests: C50, e1071, FSelector, infotheo, kknn, knitr, randomForest,
        rJava(>= 0.9), rmarkdown, rpart, RWeka(>= 0.4), testthat,
        xgboost(>= 0.6-4)
License: GPL | file LICENSE
LazyData: true
BugReports: https://github.com/rivolli/utiml
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-02-06 23:01:38 UTC; rivolli
Author: Adriano Rivolli [aut, cre]
Maintainer: Adriano Rivolli <rivolli@utfpr.edu.br>
Repository: CRAN
Date/Publication: 2020-02-07 06:30:02 UTC
