Explaining and Visualizing Random Forests in Terms of Variable Importance

A set of tools to help explain which variables are most important in a random forests. Various variable importance measures are calculated and visualized in different settings in order to get an idea on how their importance changes depending on our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran Z. Gorodeski and Andy J. Minn and Michael S. Lauer (2010) , Leo Breiman (2001) ).

Set of tools to understand what is happening inside a Random Forest. A detailed discussion of the package and importance measures it implements can be found here: Master thesis on randomForestExplainer.






Reference manual

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0.10.1 by Yue Jiang, 10 months ago


Browse source code at https://github.com/cran/randomForestExplainer

Authors: Aleksandra Paluszynska [aut] , Przemyslaw Biecek [aut, ths] , Yue Jiang [aut, cre]

Documentation:   PDF Manual  

GPL license

Imports data.table, dplyr, DT, GGally, ggplot2, ggrepel, randomForest, ranger, reshape2, rmarkdown

Suggests knitr, MASS, testthat

See at CRAN