Meta-Feature Extractor

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) .


Reference manual

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0.1.0 by Adriano Rivolli, a year ago

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Authors: Adriano Rivolli [aut, cre], Luis Paulo F. Garcia [aut], Andre C. P. L. F. de Carvalho [ths]

Documentation:   PDF Manual  

GPL | file LICENSE license

Imports C50, class, e1071, infotheo, MASS, rpart, stats, utils

Suggests knitr, rmarkdown, testthat

See at CRAN