list of importance measures

Author: pbiecek

R/measure_importance.R

@@ -79,7 +79,11 @@ measure_p_value <- function(importance_frame){
 #'
 #' @param forest A random forest produced by the function randomForest with option localImp = TRUE
 #' @param mean_sample The sample of trees on which mean minimal depth is calculated, possible values are "all_trees", "top_trees", "relevant_trees"
-#' @param measures A vector of names of importance measures to be calculated - if equal to NULL then all are calculated; if "p_value" is to be calculated then "no_of_nodes" will be too
+#' @param measures A vector of names of importance measures to be calculated - if equal to NULL then all are calculated;
+#' if "p_value" is to be calculated then "no_of_nodes" will be too. Suitable measures for \code{classification} forests are:
+#' \code{mean_min_depth}, \code{accuracy_decrease}, \code{gini_decrease}, \code{no_of_nodes},
+#' \code{times_a_root}. For \code{regression} forests choose from: \code{mean_min_depth},
+#' \code{mse_increase}, \code{node_purity_increase}, \code{no_of_nodes}, \code{times_a_root}.
 #'
 #' @return A data frame with rows corresponding to variables and columns to various measures of importance of variables
 #'