Compute variable importance with p-values.
importance_pvalues(x, method = c("janitza", "altmann"),
num.permutations = 100, formula = NULL, data = NULL, ...)ranger or holdoutRF object.
Method to compute p-values. Use "janitza" for the method by Janitza et al. (2015) or "altmann" for the non-parametric method by Altmann et al. (2010).
Number of permutations. Used in the "altmann" method only.
Object of class formula or character describing the model to fit. Used in the "altmann" method only.
Training data of class data.frame or matrix. Used in the "altmann" method only.
Further arguments passed to ranger(). Used in the "altmann" method only.
Variable importance and p-values.
Janitza, S., Celik, E. & Boulesteix, A.-L., (2015). A computationally fast variable importance test for random forests for high-dimensional data. Adv Data Anal Classif http://dx.doi.org/10.1007/s11634-016-0276-4. Altmann, A., Tolosi, L., Sander, O. & Lengauer, T. (2010). Permutation importance: a corrected feature importance measure, Bioinformatics 26(10):1340-1347.