varrank: Heuristics Tools Based on Mutual Information for Variable Ranking

A computational toolbox of heuristics approaches for performing variable ranking and feature selection based on mutual information well adapted for multivariate system epidemiology datasets. The core function is a general implementation of the minimum redundancy maximum relevance model. R. Battiti (1994) <doi:10.1109/72.298224>. Continuous variables are discretized using a large choice of rule. Variables ranking can be learned with a sequential forward/backward search algorithm. The two main problems that can be addressed by this package is the selection of the most representative variable within a group of variables of interest (i.e. dimension reduction) and variable ranking with respect to a set of features of interest.

Package details

AuthorGilles Kratzer [aut, cre] (<>), Reinhard Furrer [ctb] (<>)
MaintainerGilles Kratzer <[email protected]>
Package repositoryView on CRAN
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varrank documentation built on May 2, 2019, 5:32 a.m.