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, this package allows a comprehensive data characterization, a deep data exploration and a large number of Meta-Learning based data analysis. These concepts are described in the book: Brazdil, P., Giraud-Carrier, C., Soares, C., Vilalta, R. (2009) .

Documentation

Manual: mfe.pdf
Vignette: Vignette Title

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

Author(s): Adriano Rivolli*, Luis Paulo F. Garcia*, Andre C. P. L. F. de Carvalho*

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

install.packages("mfe")

Depends R (>= 3.3.1),
Imports C50, class, e1071, infotheo, MASS, rpart, stats, utils
Suggests knitr, rmarkdown, testthat
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Package mfe
Materials
URL https://github.com/rivolli/mfe
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Version 0.1.0
Published 2017-01-31
License GPL | file LICENSE
BugReports https://github.com/rivolli/mfe
SystemRequirements
NeedsCompilation no
Citation
CRAN checks mfe check results
Package source mfe_0.1.0.tar.gz