depend on packages for examples

Author: pfistfl

R/MeasureFairnessConstraint.R

@@ -7,7 +7,7 @@
 #' @template pta
 #' @seealso mlr_measures_fairness
 #' @export
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' # Accuracy subject to equalized odds fairness constraint:
 #' library("mlr3")
 #' t = tsk("adult_train")

R/MeasurePositiveProbability.R

@@ -6,7 +6,7 @@
 #' This is defined as count of positive predictions divided by the number of observations.
 #'
 #' @export
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' library("mlr3")
 #' # Create Positive Probability Measure
 #' t = tsk("adult_train")

R/MeasureSubgroup.R

@@ -5,7 +5,7 @@
 #'
 #' @seealso [MeasureFairness], [groupwise_metrics]
 #' @export
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' library("mlr3")
 #' # Create MeasureFairness to measure the Predictive Parity.
 #' t = tsk("adult_train")

R/PipeOpEOd.R

@@ -83,7 +83,7 @@
 #' @family PipeOps
 #' @seealso https://mlr3book.mlr-org.com/list-pipeops.html
 #' @export
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' library("mlr3")
 #' library("mlr3pipelines")
 #'

R/PipeOpReweighing.R

@@ -59,7 +59,7 @@
 #' @family PipeOps
 #' @seealso https://mlr3book.mlr-org.com/list-pipeops.html
 #' @export
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' library("mlr3")
 #' library("mlr3pipelines")
 #'

R/compare_metrics.R

@@ -29,7 +29,7 @@
 #'
 #' @export
 #' @return A 'ggplot2' object.
-#' @examples
+#' @examplesIf rlang::is_installed("rpart") && rlang::is_installed("ranger")
 #' library("mlr3")
 #' library("mlr3learners")
 #'

R/compute_metrics.R

@@ -13,7 +13,7 @@
 #' @param prediction (`vector`) \cr A vector containing predictions. 
 #' @param metrics (`Metric`|`list`) \cr (List of) mlr3 metrics to apply.
 #' @export
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' library("mlr3")
 #' # Get adult data as a data.table
 #' train = tsk("adult_train")$data()

R/fairness_accuracy_tradeoff.R

@@ -30,11 +30,12 @@
 #'     The accuracy measure that will evaluated.
 #'     Default measure set to be [msr("classif.acc")][mlr3::MeasureClassif].
 #'   * `task` ([mlr3::TaskClassif])\cr
-#'     The data task that contains the protected column, only required when the class of object is ([mlr3::PredictionClassif])
+#'     The data task that contains the protected column, only required 
+#'     when the class of object is ([mlr3::PredictionClassif])
 #'
 #' @export
 #' @return A 'ggplot2' object.
-#' @examples
+#' @examplesIf rlang::is_installed("rpart") && rlang::is_installed("ranger")
 #' library("mlr3")
 #' library("mlr3learners")
 #' library("ggplot2")

R/fairness_prediction_density.R

@@ -21,7 +21,7 @@
 #'
 #' @export
 #' @return A 'ggplot2' object.
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' library("mlr3")
 #' library("mlr3learners")
 #'

R/fairness_tensor.R

@@ -18,7 +18,7 @@
 #' @return
 #'   `list()` of confusion matrix for every group in `"pta"`.
 #' @export
-#' @examples
+#' @examplesIf rlang::is_installed("rpart")
 #' library("mlr3")
 #' task = tsk("compas")
 #' prediction = lrn("classif.rpart")$train(task)$predict(task)