varrank: an R package for variable ranking based on mutual information with applications to observed systemic datasets
This provides a tool for researchers analyzing systemic datasets, but it is incremental as it packages existing methods into software.
The authors introduced varrank, an R package for variable ranking using mutual information, specifically implementing the mRMRe model to address dimension reduction and variable ranking in multivariate datasets.
This article describes the R package varrank. It has a flexible implementation of heuristic approaches which perform variable ranking based on mutual information. The package is particularly suitable for exploring multivariate datasets requiring a holistic analysis. The core functionality is a general implementation of the minimum redundancy maximum relevance (mRMRe) model. This approach is based on information theory metrics. It is compatible with discrete and continuous data which are discretised using a large choice of possible rules. The two main problems that can be addressed by this package are the selection of the most representative variables for modeling a collection of variables of interest, i.e., dimension reduction, and variable ranking with respect to a set of variables of interest.