mlr-org · pat-s · Sep 2, 2022 · Aug 16, 2022 · Aug 16, 2022 · Aug 16, 2022
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -37,6 +37,7 @@ Suggests:
     lgr,
     mlr3learners,
     mlr3measures,
+    mlr3pipelines,
     praznik,
     rpart,
     testthat (>= 3.0.0),

diff --git a/NEWS.md b/NEWS.md
@@ -3,7 +3,7 @@
 # mlr3filters 0.5.0.9000
 
 - Add references to benchmark paper and praznik paper #104
-
+* Add documentation for PipeOpFilter
 
 # mlr3filters 0.5.0
 

diff --git a/R/FilterAUC.R b/R/FilterAUC.R
@@ -22,6 +22,18 @@
 #' filter = flt("auc")
 #' filter$calculate(task)
 #' head(as.data.table(filter), 3)
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("auc"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterAUC = R6Class("FilterAUC",
   inherit = Filter,
 

diff --git a/R/FilterAnova.R b/R/FilterAnova.R
@@ -26,6 +26,18 @@
 #'
 #' # transform to p-value
 #' 10^(-filter$scores)
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("anova"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterAnova = R6Class("FilterAnova",
   inherit = Filter,
 

diff --git a/R/FilterCMIM.R b/R/FilterCMIM.R
@@ -25,6 +25,18 @@
 #'   filter$calculate(task, nfeat = 2)
 #'   as.data.table(filter)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("cmim"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterCMIM = R6Class("FilterCMIM",
   inherit = Filter,
 

diff --git a/R/FilterCarScore.R b/R/FilterCarScore.R
@@ -20,12 +20,24 @@
 #'   filter$calculate(task)
 #'   head(as.data.table(filter), 3)
 #'
-#'   ## changing filter settings
+#'   ## changing the filter settings
 #'   filter = flt("carscore")
 #'   filter$param_set$values = list("diagonal" = TRUE)
 #'   filter$calculate(task)
 #'   head(as.data.table(filter), 3)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "care", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("mtcars")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("carscore"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("regr.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterCarScore = R6Class("FilterCarScore",
   inherit = Filter,
 

diff --git a/R/FilterCorrelation.R b/R/FilterCorrelation.R
@@ -26,6 +26,17 @@
 #' filter$param_set$values = list("method" = "spearman")
 #' filter$calculate(task)
 #' as.data.table(filter)
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("boston_housing")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("correlation"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("regr.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterCorrelation = R6Class("FilterCorrelation",
   inherit = Filter,
 

diff --git a/R/FilterDISR.R b/R/FilterDISR.R
@@ -25,6 +25,18 @@
 #'   filter$calculate(task)
 #'   as.data.table(filter)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("disr"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterDISR = R6Class("FilterDISR",
   inherit = Filter,
 

diff --git a/R/FilterFindCorrelation.R b/R/FilterFindCorrelation.R
@@ -19,7 +19,7 @@
 #' @template seealso_filter
 #' @export
 #' @examples
-#' ## Pearson (default)
+#' # Pearson (default)
 #' task = mlr3::tsk("mtcars")
 #' filter = flt("find_correlation")
 #' filter$calculate(task)
@@ -29,6 +29,18 @@
 #' filter = flt("find_correlation", method = "spearman")
 #' filter$calculate(task)
 #' as.data.table(filter)
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("find_correlation"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterFindCorrelation = R6Class("FilterFindCorrelation",
   inherit = Filter,
 

diff --git a/R/FilterImportance.R b/R/FilterImportance.R
@@ -11,11 +11,28 @@
 #' @template seealso_filter
 #' @export
 #' @examples
-#' task = mlr3::tsk("iris")
-#' learner = mlr3::lrn("classif.rpart")
-#' filter = flt("importance", learner = learner)
-#' filter$calculate(task)
-#' as.data.table(filter)
+#' if (requireNamespace("rpart")) {
+#'   task = mlr3::tsk("iris")
+#'   learner = mlr3::lrn("classif.rpart")
+#'   filter = flt("importance", learner = learner)
+#'   filter$calculate(task)
+#'   as.data.table(filter)
+#' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "mlr3learners"), quietly = TRUE)) {
+#'   library("mlr3learners")
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   learner = mlr3::lrn("classif.rpart")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("importance", learner = learner), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.log_reg"))
+#'
+#'   graph$train(task)
+#' }
 FilterImportance = R6Class("FilterImportance",
   inherit = Filter,
 

diff --git a/R/FilterInformationGain.R b/R/FilterInformationGain.R
@@ -1,3 +1,4 @@
+
 #' @title Information Gain Filter
 #'
 #' @name mlr_filters_information_gain
@@ -29,6 +30,20 @@
 #'   filterGR$param_set$values = list("type" = "gainratio")
 #'   filterGR$calculate(task)
 #'   head(as.data.table(filterGR), 3)
+#'
+#' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "FSelectorRcpp", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("information_gain"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#'
 #' }
 FilterInformationGain = R6Class("FilterInformationGain",
   inherit = Filter,

diff --git a/R/FilterJMI.R b/R/FilterJMI.R
@@ -1,3 +1,4 @@
+
 #' @title Joint Mutual Information Filter
 #'
 #' @name mlr_filters_jmi
@@ -14,7 +15,6 @@
 #'
 #' `r format_bib("bommert_2020")`
 #'
-#'
 #' @template details_praznik
 #' @family Filter
 #' @template seealso_filter
@@ -26,6 +26,18 @@
 #'   filter$calculate(task, nfeat = 2)
 #'   as.data.table(filter)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("jmi"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterJMI = R6Class("FilterJMI",
   inherit = Filter,
 

diff --git a/R/FilterJMIM.R b/R/FilterJMIM.R
@@ -25,6 +25,18 @@
 #'   filter$calculate(task, nfeat = 2)
 #'   as.data.table(filter)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("jmim"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterJMIM = R6Class("FilterJMIM",
   inherit = Filter,
 

diff --git a/R/FilterKruskalTest.R b/R/FilterKruskalTest.R
@@ -25,6 +25,18 @@
 #'
 #' # transform to p-value
 #' 10^(-filter$scores)
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("kruskal_test"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterKruskalTest = R6Class("FilterKruskalTest",
   inherit = Filter,
 

diff --git a/R/FilterMIM.R b/R/FilterMIM.R
@@ -25,6 +25,18 @@
 #'   filter$calculate(task, nfeat = 2)
 #'   as.data.table(filter)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("mim"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterMIM = R6Class("FilterMIM",
   inherit = Filter,
 

diff --git a/R/FilterMRMR.R b/R/FilterMRMR.R
@@ -25,6 +25,18 @@
 #'   filter$calculate(task, nfeat = 2)
 #'   as.data.table(filter)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("mrmr"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterMRMR = R6Class("FilterMRMR",
   inherit = Filter,
 

diff --git a/R/FilterNJMIM.R b/R/FilterNJMIM.R
@@ -25,6 +25,18 @@
 #'   filter$calculate(task, nfeat = 2)
 #'   as.data.table(filter)
 #' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("njmim"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterNJMIM = R6Class("FilterNJMIM",
   inherit = Filter,
 

diff --git a/R/FilterPerformance.R b/R/FilterPerformance.R
@@ -12,11 +12,25 @@
 #' @template seealso_filter
 #' @export
 #' @examples
-#' task = mlr3::tsk("iris")
-#' learner = mlr3::lrn("classif.rpart")
-#' filter = flt("performance", learner = learner)
-#' filter$calculate(task)
-#' as.data.table(filter)
+#' if (requireNamespace("rpart")) {
+#'   task = mlr3::tsk("iris")
+#'   learner = mlr3::lrn("classif.rpart")
+#'   filter = flt("performance", learner = learner)
+#'   filter$calculate(task)
+#'   as.data.table(filter)
+#' }
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "rpart"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'   l = lrn("classif.rpart")
+#'
+#'   # Note: `filter.frac` is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("performance", learner = l), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterPerformance = R6Class("FilterPerformance",
   inherit = Filter,