Docs

DESCRIPTION

@@ -31,13 +31,12 @@ Imports:
 Suggests:
     care,
     caret,
-    carSurv,
     FSelectorRcpp,
     knitr,
     lgr,
     mlr3learners,
     mlr3measures,
-    mlr3proba,
+    mlr3pipelines,
     praznik,
     rpart,
     testthat (>= 3.0.0),
@@ -47,15 +46,13 @@ Config/testthat/parallel: true
 Encoding: UTF-8
 NeedsCompilation: no
 Roxygen: list(markdown = TRUE, r6 = TRUE)
-RoxygenNote: 7.2.0
+RoxygenNote: 7.2.1
 Collate:
     'Filter.R'
     'mlr_filters.R'
     'FilterAUC.R'
     'FilterAnova.R'
     'FilterCMIM.R'
-    'FilterCarScore.R'
-    'FilterCarSurvScore.R'
     'FilterCorrelation.R'
     'FilterDISR.R'
     'FilterFindCorrelation.R'
@@ -75,5 +72,6 @@ Collate:
     'bibentries.R'
     'flt.R'
     'helper.R'
+    'rd_info.R'
     'reexports.R'
     'zzz.R'

NAMESPACE

@@ -2,12 +2,11 @@
 
 S3method(as.data.table,DictionaryFilter)
 S3method(as.data.table,Filter)
+S3method(rd_info,Filter)
 export(Filter)
 export(FilterAUC)
 export(FilterAnova)
 export(FilterCMIM)
-export(FilterCarScore)
-export(FilterCarSurvScore)
 export(FilterCorrelation)
 export(FilterDISR)
 export(FilterFindCorrelation)

R/FilterAUC.R

@@ -14,6 +14,8 @@
 #'
 #' `r format_bib("bommert_2020")`
 #'
+#' @templateVar id auc
+#' @template filter
 #' @family Filter
 #' @template seealso_filter
 #' @export
@@ -22,6 +24,18 @@
 #' filter = flt("auc")
 #' filter$calculate(task)
 #' head(as.data.table(filter), 3)
+#'
+#' if (requireNamespace("mlr3pipelines")) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: The filter.frac is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("auc"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterAUC = R6Class("FilterAUC",
   inherit = Filter,
 

R/FilterAnova.R

@@ -14,6 +14,8 @@
 #'
 #' `r format_bib("bommert_2020")`
 #'
+#' @templateVar id anova
+#' @template filter
 #' @family Filter
 #' @importFrom stats aov
 #' @template seealso_filter
@@ -26,6 +28,18 @@
 #'
 #' # transform to p-value
 #' 10^(-filter$scores)
+#'
+#' if (requireNamespace("mlr3pipelines")) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: The filter.frac is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("anova"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("classif.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterAnova = R6Class("FilterAnova",
   inherit = Filter,
 

R/FilterCMIM.R

@@ -14,15 +14,31 @@
 #'
 #' `r format_bib("bommert_2020")`
 #'
+#' @templateVar id cmim
+#' @template filter
 #' @template details_praznik
 #' @family Filter
 #' @template seealso_filter
 #' @export
 #' @examples
-#' task = mlr3::tsk("iris")
-#' filter = flt("cmim")
-#' filter$calculate(task, nfeat = 2)
-#' as.data.table(filter)
+#' if (requireNamespace("praznik")) {
+#'   task = mlr3::tsk("iris")
+#'   filter = flt("cmim")
+#'   filter$calculate(task, nfeat = 2)
+#'   as.data.table(filter)
+#' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: The 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,
 

R/FilterCarSurvScore.R

@@ -9,16 +9,11 @@
 #' @references
 #' `r format_bib("bommert_2021")`
 #'
+#' @templateVar id surv.carfsurvscore
+#' @template filter
 #' @family Filter
 #' @template seealso_filter
 #' @export
-#' @examples
-#' if (requireNamespace("mlr3proba")) {
-#'   task = mlr3::tsk("gbcs")
-#'   filter = flt("carsurvscore")
-#'   filter$calculate(task)
-#'   head(as.data.table(filter), 3)
-#' }
 FilterCarSurvScore = R6Class("FilterCarSurvScore",
   inherit = Filter,
 

R/FilterCorrelation.R

@@ -11,6 +11,8 @@
 #'
 #' `r format_bib("bommert_2020")`
 #'
+#' @templateVar id correlation
+#' @template filter
 #' @family Filter
 #' @template seealso_filter
 #' @export
@@ -26,6 +28,17 @@
 #' filter$param_set$values = list("method" = "spearman")
 #' filter$calculate(task)
 #' as.data.table(filter)
+#' if (requireNamespace("mlr3pipelines")) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("boston_housing")
+#'
+#'   # Note: The filter.frac is selected randomly and should be tuned.
+#'
+#'   graph = po("filter", filter = flt("correlation"), filter.frac = 0.5) %>>%
+#'     po("learner", mlr3::lrn("regr.rpart"))
+#'
+#'   graph$train(task)
+#' }
 FilterCorrelation = R6Class("FilterCorrelation",
   inherit = Filter,
 

R/FilterDISR.R

@@ -14,15 +14,31 @@
 #'
 #' `r format_bib("bommert_2020")`
 #'
+#' @templateVar id disr
+#' @template filter
 #' @template details_praznik
 #' @family Filter
 #' @template seealso_filter
 #' @export
 #' @examples
-#' task = mlr3::tsk("iris")
-#' filter = flt("disr")
-#' filter$calculate(task)
-#' as.data.table(filter)
+#' if (requireNamespace("praznik")) {
+#'   task = mlr3::tsk("iris")
+#'   filter = flt("disr")
+#'   filter$calculate(task)
+#'   as.data.table(filter)
+#' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "praznik"), quietly = TRUE)) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: The 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,
 

R/FilterFindCorrelation.R

@@ -15,11 +15,14 @@
 #' Subsequently `caret::findCorrelation(cutoff = 0.9)` lists the same features
 #' that are excluded with `FilterFindCorrelation` at score 0.1 (= 1 - 0.9).
 #'
+#' @templateVar id find_correlation
+#' @template filter
+#'
 #' @family Filter
 #' @template seealso_filter
 #' @export
 #' @examples
-#' ## Pearson (default)
+#' # Pearson (default)
 #' task = mlr3::tsk("mtcars")
 #' filter = flt("find_correlation")
 #' filter$calculate(task)
@@ -29,6 +32,18 @@
 #' filter = flt("find_correlation", method = "spearman")
 #' filter$calculate(task)
 #' as.data.table(filter)
+#'
+#' if (requireNamespace("mlr3pipelines")) {
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   # Note: The 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,
 

R/FilterImportance.R

@@ -7,15 +7,35 @@
 #' extracting the variable importance (property "importance"), fits the model
 #' and extracts the importance values to use as filter scores.
 #'
+#' @templateVar id importance
+#' @template filter
+#'
 #' @family Filter
 #' @template seealso_filter
 #' @export
 #' @examples
-#' task = mlr3::tsk("iris")
-#' learner = mlr3::lrn("classif.rpart")
-#' filter = flt("importance", learner = learner)
-#' filter$calculate(task)
-#' as.data.table(filter)
+#' if (requireNamespace("MASS")) {
+#'   task = mlr3::tsk("iris")
+#'   learner = mlr3::lrn("classif.rpart")
+#'   filter = flt("importance", learner = learner)
+#'   filter$calculate(task)
+#'   as.data.table(filter)
+#' }
+#'
+#' if (mlr3misc::require_namespaces(c("mlr3pipelines", "mlr3learners", "MASS"), quietly = TRUE)) {
+#'   library("mlr3learners")
+#'   library("mlr3pipelines")
+#'   task = mlr3::tsk("spam")
+#'
+#'   learner = mlr3::lrn("classif.rpart")
+#'
+#'   # Note: The 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.lda"))
+#'
+#'   graph$train(task)
+#' }
 FilterImportance = R6Class("FilterImportance",
   inherit = Filter,