ls.relative

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: Rivolli A., Garcia L.,
Soares c., Vanschoren J. and Carvalho A. (2018) <arXiv:1808.10406>.

Adriano Rivolli

Meta-Feature Extractor

ls.relative: List the relative meta-features

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