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## 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.

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## What's New 

- 13/10/2022 - change of maintainer (v 0.5)

- 26/04/2021 - small updates (v 0.4)

- 29/01/2020 - small updates (v 0.3)

- 20/12/2018 - new varrank website made with `pkgdown` (v 0.2)

- 23/04/2018 - varrank is available on CRAN (v 0.1)

- 19/04/2018 - new pre-print [varrank: an R package for variable ranking based on mutual information with applications to observed systemic datasets](https://arxiv.org/pdf/1804.07134.pdf) on arXiv

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**`varrank` is developed and maintained by [Gilles Kratzer](https://gilleskratzer.netlify.com/) and [Prof. Reinhard Furrer](https://user.math.uzh.ch/furrer/) from 
[Applied Statistics Group](https://www.math.uzh.ch/as/index.php?id=as) at University of Zurich.**

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