fix: ranger parameters (#277)

* fix: ignore time.interest parameter * feat: add node.stats parameter * fix: minprop
mlr-org · Nov 17, 2023 · 1a4d571 · 1a4d571
1 parent 5d5ecb7
commit 1a4d571
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Showing 4 changed files with 4 additions and 4 deletions.
diff --git a/R/LearnerClassifRanger.R b/R/LearnerClassifRanger.R
@@ -46,10 +46,10 @@ LearnerClassifRanger = R6Class("LearnerClassifRanger",
         max.depth                    = p_int(default = NULL, lower = 0L, special_vals = list(NULL), tags = "train"),
         min.bucket                   = p_int(1L, default = 1L, tags = "train"),
         min.node.size                = p_int(1L, default = NULL, special_vals = list(NULL), tags = "train"),
-        min.prop                     = p_dbl(default = 0.1, tags = "train"),
         minprop                      = p_dbl(default = 0.1, tags = "train"),
         mtry                         = p_int(lower = 1L, special_vals = list(NULL), tags = "train"),
         mtry.ratio                   = p_dbl(lower = 0, upper = 1, tags = "train"),
+        node.stats                   = p_lgl(default = FALSE, tags = "train"),
         num.random.splits            = p_int(1L, default = 1L, tags = "train"),
         num.threads                  = p_int(1L, default = 1L, tags = c("train", "predict", "threads")),
         num.trees                    = p_int(1L, default = 500L, tags = c("train", "predict", "hotstart")),

diff --git a/R/LearnerRegrRanger.R b/R/LearnerRegrRanger.R
@@ -35,10 +35,10 @@ LearnerRegrRanger = R6Class("LearnerRegrRanger",
         max.depth                    = p_int(default = NULL, lower = 0L, special_vals = list(NULL), tags = "train"),
         min.bucket                   = p_int(1L, default = 1L, tags = "train"),
         min.node.size                = p_int(1L, default = 5L, special_vals = list(NULL), tags = "train"),
-        min.prop                     = p_dbl(default = 0.1, tags = "train"),
         minprop                      = p_dbl(default = 0.1, tags = "train"),
         mtry                         = p_int(lower = 1L, special_vals = list(NULL), tags = "train"),
         mtry.ratio                   = p_dbl(lower = 0, upper = 1, tags = "train"),
+        node.stats                   = p_lgl(default = FALSE, tags = "train"),
         num.random.splits            = p_int(1L, default = 1L, tags = "train"),
         num.threads                  = p_int(1L, default = 1L, tags = c("train", "predict", "threads")),
         num.trees                    = p_int(1L, default = 500L, tags = c("train", "predict", "hotstart")),

diff --git a/inst/paramtest/test_paramtest_classif.ranger.R b/inst/paramtest/test_paramtest_classif.ranger.R
@@ -18,7 +18,7 @@ test_that("classif.ranger", {
     "status.variable.name", # handled via mlr3
     "classification", # handled via mlr3
     "mtry.ratio", # custom hyperpar
-    "min.prop" # renamed to minprop in upstream package
+    "time.interest" # survival only
   )
 
   ParamTest = run_paramtest(learner, fun, exclude, tag = "train")

diff --git a/inst/paramtest/test_paramtest_regr.ranger.R b/inst/paramtest/test_paramtest_regr.ranger.R
@@ -17,7 +17,7 @@ test_that("regr.ranger", {
     "status.variable.name", # handled via mlr3
     "classification", # handled via mlr3
     "mtry.ratio", # custom hyperpar
-    "min.prop" # renamed to minprop in upstream package
+    "time.interest" # survival only
   )
 
   ParamTest = run_paramtest(learner, fun, exclude, tag = "train")