fix: remove unsupported predict parameters from xgboost (#356)

* fix: remove unsupported predict parameters from xgboost

* ...

* ...

* ...

* ...

Author: be-marc

NAMESPACE

@@ -34,6 +34,7 @@ import(paradox)
 importFrom(R6,R6Class)
 importFrom(mlr3,LearnerClassif)
 importFrom(mlr3,LearnerRegr)
+importFrom(mlr3,assert_quantiles)
 importFrom(mlr3,assert_validate)
 importFrom(mlr3,mlr_learners)
 importFrom(stats,predict)

R/LearnerClassifXgboost.R

@@ -129,10 +129,6 @@ LearnerClassifXgboost = R6Class("LearnerClassifXgboost",
         num_parallel_tree           = p_int(1L, default = 1L, tags = c("train", "control")),
         objective                   = p_uty(default = "binary:logistic", tags = c("train", "predict", "control")),
         one_drop                    = p_lgl(default = FALSE, tags = "train", depends = quote(booster == "dart")),
-        outputmargin                = p_lgl(default = FALSE, tags = "predict"),
-        predcontrib                 = p_lgl(default = FALSE, tags = "predict"),
-        predinteraction             = p_lgl(default = FALSE, tags = "predict"),
-        predleaf                    = p_lgl(default = FALSE, tags = "predict"),
         print_every_n               = p_int(1L, default = 1L, tags = "train", depends = quote(verbose == 1L)),
         process_type                = p_fct(c("default", "update"), default = "default", tags = "train"),
         rate_drop                   = p_dbl(0, 1, default = 0, tags = "train", depends = quote(booster == "dart")),
@@ -222,6 +218,10 @@ LearnerClassifXgboost = R6Class("LearnerClassifXgboost",
       lvls = task$class_names
       nlvls = length(lvls)
 
+      if (isTRUE(pv$predcontrib) || isTRUE(pv$predinteraction) || isTRUE(pv$predleaf)) {
+        warningf("Predicting contributions, interactions, or leaf values with $predict() is not supported. ")
+      }
+
       if (is.null(pv$objective)) {
         pv$objective = if (nlvls == 2L) "binary:logistic" else "multi:softprob"
       }

R/LearnerRegrXgboost.R

@@ -109,10 +109,6 @@ LearnerRegrXgboost = R6Class("LearnerRegrXgboost",
         num_parallel_tree           = p_int(1L, default = 1L, tags = "train"),
         objective                   = p_uty(default = "reg:squarederror", tags = c("train", "predict")),
         one_drop                    = p_lgl(default = FALSE, tags = "train", depends = quote(booster == "dart")),
-        outputmargin                = p_lgl(default = FALSE, tags = "predict"),
-        predcontrib                 = p_lgl(default = FALSE, tags = "predict"),
-        predinteraction             = p_lgl(default = FALSE, tags = "predict"),
-        predleaf                    = p_lgl(default = FALSE, tags = "predict"),
         print_every_n               = p_int(1L, default = 1L, tags = "train", depends = quote(verbose == 1L)),
         process_type                = p_fct(c("default", "update"), default = "default", tags = "train"),
         rate_drop                   = p_dbl(0, 1, default = 0, tags = "train", depends = quote(booster == "dart")),

R/zzz.R

@@ -3,7 +3,7 @@
 #' @import mlr3misc
 #' @import checkmate
 #' @importFrom R6 R6Class
-#' @importFrom mlr3 mlr_learners LearnerClassif LearnerRegr assert_validate
+#' @importFrom mlr3 mlr_learners LearnerClassif LearnerRegr assert_validate assert_quantiles
 #' @importFrom stats predict reformulate
 #' @importFrom utils packageVersion
 #'

inst/paramtest/test_paramtest_classif.xgboost.R

@@ -60,7 +60,11 @@ test_that("predict classif.xgboost", {
   exclude = c(
     "object", # handled by mlr3
     "newdata", # handled by mlr3o
-    "objective" # defined in xgboost::xgboost and already in param set
+    "objective", # defined in xgboost::xgboost and already in param set
+    "outputmargin", # not supported
+    "predcontrib", # not supported
+    "predinteraction", # not supported
+    "predleaf" # not supported
   )
 
   ParamTest = run_paramtest(learner, fun, exclude, tag = "predict")

inst/paramtest/test_paramtest_regr.xgboost.R

@@ -60,7 +60,11 @@ test_that("predict regr.xgboost", {
   exclude = c(
     "object", # handled by mlr3
     "newdata", # handled by mlr3
-    "objective" # defined in xgboost::xgboost and already in param set
+    "objective", # defined in xgboost::xgboost and already in param set
+    "outputmargin", # not supported
+    "predcontrib", # not supported
+    "predinteraction", # not supported
+    "predleaf" # not supported
   )
 
   ParamTest = run_paramtest(learner, fun, exclude, tag = "predict")

man-roxygen/note_xgboost.R

@@ -2,3 +2,7 @@
 #' To compute on GPUs, you first need to compile \CRANpkg{xgboost} yourself and link
 #' against CUDA.
 #' See \url{https://xgboost.readthedocs.io/en/stable/build.html#building-with-gpu-support}.
+#'
+#' The `outputmargin`, `predcontrib`, `predinteraction`, and `predleaf` parameters are not supported.
+#' You can still call e.g. `predict(learner$model, newdata = newdata, outputmargin = TRUE)` to get these predictions.
+