Prepare new CRAN release

DESCRIPTION

@@ -1,10 +1,12 @@
 Package: ranger
 Type: Package
 Title: A Fast Implementation of Random Forests
-Version: 0.16.4
-Date: 2024-10-28
-Author: Marvin N. Wright [aut, cre], Stefan Wager [ctb], Philipp Probst [ctb]
-Maintainer: Marvin N. Wright <[email protected]>
+Version: 0.17.0
+Date: 2024-11-08
+Authors@R: c(
+    person("Marvin N.", "Wright", email = "[email protected]", role = c("aut", "cre")),
+    person("Stefan", "Wager", role = "ctb"),
+    person("Philipp", "Probst", role = "ctb"))
 Description: A fast implementation of Random Forests, particularly suited for high
           dimensional data. Ensembles of classification, regression, survival and
           probability prediction trees are supported. Data from genome-wide association

NAMESPACE

@@ -11,6 +11,8 @@ S3method(print,deforest.ranger)
 S3method(print,ranger)
 S3method(print,ranger.forest)
 S3method(print,ranger.prediction)
+S3method(str,ranger)
+S3method(str,ranger.forest)
 S3method(timepoints,ranger)
 S3method(timepoints,ranger.prediction)
 export(csrf)

NEWS

@@ -1,4 +1,12 @@
 
+##### Version 0.17.0
+* Set num.threads=2 as default; respect environment variables and options
+* Add handling of missing values for classification and regression
+* Allow vector min.node.size and min.bucket for class-specific limits
+* Add Poisson splitting rule for regression trees
+* Add hierarchical shrinkage
+* Fix a bug for always.split.variables (for some settings)
+
 ##### Version 0.16.0
 * Add node.stats option to save node statistics of all nodes
 * Add time.interest option to restrict unique survival times (faster and saves memory)

NEWS.md

@@ -1,4 +1,7 @@
 
+# ranger 0.17.0
+* New CRAN version
+
 # ranger 0.16.4
 * Add handling of missing values for classification and regression
 

R/hshrink.R

@@ -39,6 +39,9 @@
 #' @return The ranger object is modified in-place. 
 #'
 #' @examples
+#' ## Hierarchical shrinkage for a probablity forest
+#' rf <- ranger(Species ~ ., iris, node.stats = TRUE, probability = TRUE)
+#' hshrink(rf, lambda = 5)
 ##' @references
 ##' \itemize{
 ##'   \item Agarwal, A., Tan, Y.S., Ronen, O., Singh, C. & Yu, B. (2022). Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models. Proceedings of the 39th International Conference on Machine Learning, PMLR 162:111-135.

R/print.R

@@ -103,11 +103,13 @@ print.ranger.prediction <- function(x, ...) {
   }
 }
 
+##' @export
 str.ranger.forest <- function(object, max.level = 2, ...) {
   class(object) <- "list"
   str(object, max.level = max.level, ...)
 }
 
+##' @export
 str.ranger <- function(object, max.level = 2, ...) {
   class(object) <- "list"
   str(object, max.level = max.level, ...)

cpp_version/src/version.h

@@ -1,3 +1,3 @@
 #ifndef RANGER_VERSION
-#define RANGER_VERSION "0.16.3"
+#define RANGER_VERSION "0.17.0"
 #endif