DESCRIPTION

Package: mfe
Type: Package
Title: Meta-Feature Extractor
Version: 0.1.3
Date: 2019-08-26
Authors@R: c(person("Adriano", "Rivolli", email="rivolli@utfpr.edu.br", 
  role=c("aut", "cre")), person("Luis", "P. F. Garcia", 
  email="luis.garcia@unb.br", role="aut"), person("Andre", 
  "C. P. L. F. de Carvalho", email="andre@icmc.usp.br", role="ths"))
Description: Extracts meta-features from datasets to support the design of 
  recommendation systems based on Meta-Learning. The meta-features, also called 
  characterization measures, are able to characterize the complexity of datasets
  and to provide estimates of algorithm performance. The package contains not 
  only the standard characterization measures, but also more recent 
  characterization measures. By making available a large set of meta-feature 
  extraction functions, tasks like comprehensive data characterization, deep 
  data exploration and large number of Meta-Learning based data analysis can be
  performed. These concepts are described in the paper: Adriano Rivolli, Luis 
  Garcia, Carlos Soares, Joaquin Vanschoren, and Andre de Carvalho. Towards 
  Reproducible Empirical Research in Meta-Learning.
URL: https://github.com/rivolli/mfe
Depends:
    R (>= 3.3),
Imports:
    cluster,
    clusterCrit,
    e1071,
    infotheo,
    MASS,
    rpart,
    rrcov,
    stats,
    utils
Suggests:
    knitr,
    rmarkdown,
    testthat
License: MIT + file LICENSE
LazyData: true
BugReports: https://github.com/rivolli/mfe/issues
RoxygenNote: 6.1.1
VignetteBuilder: knitr