Explaining and Visualizing Random Forests in Terms of Variable Importance
Plot the distribution of minimal depth in a random forest
Plot the top mean conditional minimal depth
Explain a random forest
Extract k most important variables in a random forest
Importance of variables in a random forest
Calculate minimal depth distribution of a random forest
Calculate mean conditional minimal depth
Plot importance measures with ggpairs
Plot importance measures rankings with ggpairs
Multi-way importance plot
Plot the prediction of the forest for a grid of values of two numerica...
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) <doi:10.1198/jasa.2009.tm08622>, Leo Breiman (2001) <doi:10.1023/A:1010933404324>).