DESCRIPTION

Package: utiml
Type: Package
Title: Utilities for Multi-Label Learning
Version: 0.1.7
Date: 2021-05-26
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,
    infotheo,
    kknn,
    knitr,
    randomForest,
    rmarkdown,
    markdown,
    rpart,
    testthat,
    xgboost(>= 0.6-4)
License: GPL-3
LazyData: true
BugReports: https://github.com/rivolli/utiml
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Encoding: UTF-8