Merge pull request #960 from mlr-org/PipeOpFixFactors-&-PipeOpTargetInvert---Examples

Add examples for PipeOpTargetInvert and PipeOpFixFactors

Author: mb706

R/PipeOpFixFactors.R

@@ -45,12 +45,30 @@
 #' @section Methods:
 #' Only methods inherited from [`PipeOpTaskPreprocSimple`]/[`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
+#' @examples
+#' library("mlr3")
+#'
+#' # Reduced task with no entries for the installment_rate < 20 is defined
+#' task = tsk("german_credit")
+#' rows = task$row_ids[task$data()[, installment_rate != "< 20"]]
+#' reduced_task = task$clone(deep = TRUE)$filter(rows)
+#' levels(reduced_task$data()$installment_rate)
+#'
+#' # PipeOp is trained on the reduced task
+#' po = po("fixfactors")
+#' processed_task = preproc(reduced_task, po)
+#' levels(processed_task$data()$installment_rate)
+#' summary(processed_task$data()$installment_rate)
+#'
+#' predicted_task = preproc(task, po, predict = TRUE)
+#'
+#' # Predictions are made on the task without any missing data
+#' levels(predicted_task$data()$installment_rate)
+#' summary(predicted_task$data()$installment_rate)
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOpTaskPreproc.R
 #' @export
-#' @examples
-#' library("mlr3")
 PipeOpFixFactors = R6Class("PipeOpFixFactors",
   inherit = PipeOpTaskPreprocSimple,
   public = list(

R/PipeOpTrafo.R

@@ -221,6 +221,37 @@ PipeOpTargetTrafo = R6Class("PipeOpTargetTrafo",
 #' @section Methods:
 #' Only methods inherited from [`PipeOp`].
 #'
+#' @examplesIf requireNamespace("rpart")
+#' library(mlr3)
+#' task = tsk("boston_housing")
+#' po = PipeOpTargetMutate$new("logtrafo", param_vals = list(
+#'   trafo = function(x) log(x, base = 2),
+#'   inverter = function(x) list(response = 2 ^ x$response))
+#' )
+#' # Note that this example is ill-equipped to work with
+#' # `predict_type == "se"` predictions.
+#'
+#' po$train(list(task))
+#' po$predict(list(task))
+#'
+#' g = Graph$new()
+#' g$add_pipeop(po)
+#' g$add_pipeop(LearnerRegrRpart$new())
+#' g$add_pipeop(PipeOpTargetInvert$new())
+#' g$add_edge(src_id = "logtrafo", dst_id = "targetinvert",
+#'   src_channel = 1, dst_channel = 1)
+#' g$add_edge(src_id = "logtrafo", dst_id = "regr.rpart",
+#'   src_channel = 2, dst_channel = 1)
+#' g$add_edge(src_id = "regr.rpart", dst_id = "targetinvert",
+#'   src_channel = 1, dst_channel = 2)
+#'
+#' g$train(task)
+#' g$predict(task)
+#'
+#' #syntactic sugar using ppl():
+#' tt = ppl("targettrafo", graph = PipeOpLearner$new(LearnerRegrRpart$new()))
+#' tt$param_set$values$targetmutate.trafo = function(x) log(x, base = 2)
+#' tt$param_set$values$targetmutate.inverter = function(x) list(response = 2 ^ x$response)
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOp.R