patches

* Fixed ranger and rpart parameters
* Move SVM to suggests
* Fixed UnoC documentation

Author: Raphael

DESCRIPTION

@@ -42,8 +42,7 @@ Imports:
     mlr3pipelines,
     paradox (>= 0.1.0),
     R6,
-    survival,
-    survivalsvm
+    survival
 Suggests:
     flexsurv,
     gbm,
@@ -59,6 +58,7 @@ Suggests:
     rpart,
     simsurv,
     survAUC,
+    survivalsvm,
     testthat
 VignetteBuilder:
     knitr

NAMESPACE

@@ -63,9 +63,6 @@ importFrom(stats,model.frame)
 importFrom(stats,model.matrix)
 importFrom(stats,reformulate)
 importFrom(survival,Surv)
-importFrom(survivalsvm,makediff1)
-importFrom(survivalsvm,makediff2)
-importFrom(survivalsvm,makediff3)
 importFrom(utils,data)
 importFrom(utils,head)
 importFrom(utils,tail)

NEWS.md

@@ -3,8 +3,10 @@
 * Added `method` argument to integrated scores and added weighting by bin-width
 * Added notes to IGS documentation regarding default methods and comparison to other packages
 * Added `method` to `MeasureSurvIntegrated` constructor and fields
-* Fixed mistake in `TaskSurv` documentation
+* Fixed mistake in documentation of: `TaskSurv`, `MeasureSurvUnoC`
 * Fixed errors in r-patched-solaris
+* Added missing `LearnerSurvRpart` parameter `parms` and `cost`
+
 
 # mlr3proba 0.1.0
 

R/LearnerSurvRanger.R

@@ -31,7 +31,7 @@ LearnerSurvRanger = R6Class("LearnerSurvRanger", inherit = LearnerSurv,
             ParamLgl$new(id = "replace", default = TRUE, tags = "train"),
             ParamDbl$new(id = "sample.fraction", lower = 0L, upper = 1L, tags = "train"), # for replace == FALSE, def = 0.632
             # ParamDbl$new(id = "class.weights", defaul = NULL, tags = "train"), #
-            ParamFct$new(id = "splitrule", levels = c("variance", "extratrees", "maxstat"), default = "variance", tags = "train"),
+            ParamFct$new(id = "splitrule", levels = c("logrank","extratrees","C","maxstat"), default = "logrank", tags = "train"),
             ParamInt$new(id = "num.random.splits", lower = 1L, default = 1L, tags = "train"), # requires = quote(splitrule == "extratrees")
             ParamDbl$new(id = "split.select.weights", lower = 0, upper = 1, tags = "train"),
             ParamUty$new(id = "always.split.variables", tags = "train"),

R/LearnerSurvRpart.R

@@ -18,12 +18,14 @@ LearnerSurvRpart = R6Class("LearnerSurvRpart", inherit = LearnerSurv,
   public = list(
     initialize = function() {
       ps = ParamSet$new(list(
+        ParamDbl$new("parms", default = 1, tags = "train"),
         ParamInt$new("minsplit", default = 20L, lower = 1L, tags = "train"),
         ParamDbl$new("cp", default = 0.01, lower = 0, upper = 1, tags = "train"),
         ParamInt$new("maxcompete", default = 4L, lower = 0L, tags = "train"),
         ParamInt$new("maxsurrogate", default = 5L, lower = 0L, tags = "train"),
         ParamInt$new("maxdepth", default = 30L, lower = 1L, upper = 30L, tags = "train"),
-        ParamInt$new("xval", default = 10L, lower = 0L, tags = "train")
+        ParamInt$new("xval", default = 10L, lower = 0L, tags = "train"),
+        ParamUty$new("cost", tags = "train")
       ))
       ps$values = list(xval = 0L)
 

R/LearnerSurvSVM.R

@@ -1,4 +1,3 @@
-#' @importFrom survivalsvm makediff1 makediff2 makediff3
 #' @template surv_learner
 #' @templateVar title Regression, Ranking and Hybrid Support Vector Machines
 #' @templateVar fullname LearnerSurvSVM
@@ -25,12 +24,6 @@
 #' Artificial Intelligence in Medicine, 53, 107-118.
 #'
 #' @export
-#' @examples
-#' library(mlr3)
-#' task = tgen("simsurv")$generate(20)
-#' learner = lrn("surv.svm")
-#' resampling = rsmp("cv", folds = 2)
-#' resample(task, learner, resampling)
 LearnerSurvSVM = R6Class("LearnerSurvSVM", inherit = LearnerSurv,
   public = list(
     initialize = function() {

R/MeasureSurvUnoC.R

@@ -3,9 +3,6 @@
 #' @templateVar inherit [MeasureSurv]
 #' @templateVar fullname MeasureSurvUnoC
 #' @templateVar shortname surv.unoC
-#' @templateVar pars times, lp_thresh
-#' @templateVar times_par TRUE
-#' @templateVar thresh_par TRUE
 #'
 #' @description
 #' Calls [survAUC::UnoC()].

man/LearnerSurvSVM.Rd

@@ -1,6 +1,9 @@
 context("surv.svm")
 
 test_that("autotest", {
+  makediff1 = survivalsvm::makediff1
+  makediff2 = survivalsvm::makediff2
+  makediff3 = survivalsvm::makediff3
   learner = mlr_learners$get("surv.svm")
   expect_learner(learner)
   result = run_autotest(learner,exclude = "feat_single")