some more doclinks

Author: pfistfl

R/PipeOpEOd.R

@@ -38,7 +38,9 @@
 #' @title Equalized Odds Debiasing
 #' @usage NULL
 #' @name mlr_pipeops_equalized_odds
-#' @format \link[R6:R6Class]{R6::R6Class} object inheriting from \link[mlr3pipelines:PipeOpTaskPreproc]{mlr3pipelines::PipeOpTaskPreproc}/\link[mlr3pipelines:PipeOp]{mlr3pipelines::PipeOp}.
+#' @format \link[R6:R6Class]{R6::R6Class} object inheriting from 
+#' \link[mlr3pipelines:PipeOpTaskPreproc]{mlr3pipelines::PipeOpTaskPreproc}/
+#' \link[mlr3pipelines:PipeOp]{mlr3pipelines::PipeOp}.
 #'
 #' @description
 #'   Fairness post-processing method to achieve equalized odds fairness.
@@ -57,26 +59,26 @@
 #' * `param_vals` (`list()`)
 #'
 #' @section Input and Output Channels:
-#' Input and output channels are inherited from [PipeOpTaskPreproc]. Instead of a [`Task`][mlr3::Task], a
-#' [TaskClassif][mlr3::TaskClassif] is used as input and output during training and prediction.
+#' Input and output channels are inherited from [mlr3pipelines::PipeOpTaskPreproc]. Instead of a [mlr3::Task], a
+#' [mlr3::TaskClassif] is used as input and output during training and prediction.
 #'
-#' The output during training is the input [Task][mlr3::Task]. The output during prediction is
-#' a [PredictionClassif][mlr3::PredictionClassif] with partially flipped predictions.
+#' The output during training is the input [mlr3::Task]. The output during prediction is
+#' a [mlr3::PredictionClassif] with partially flipped predictions.
 #'
 #' @section State:
-#' The `$state` is a named `list` with the `$state` elements inherited from [PipeOpTaskPreproc].
+#' The `$state` is a named list with the `$state` elements inherited from [mlr3pipelines::PipeOpTaskPreproc].
 #'
 #' @section Parameters:
-#'  * `alpha` (`numeric()`): A number between 0 (no debiasing) and 1 (full debiasing).
+#'  * `alpha` (numeric): A number between 0 (no debiasing) and 1 (full debiasing).
 #'    Controls the debiasing strength by multiplying the flipping probabilities with alpha.
-#'  * `privileged` (`character()`): The privileged group.
+#'  * `privileged` (character): The privileged group.
 #'
 #'
 #' @section Fields:
-#' Only fields inherited from [PipeOpTaskPreproc]/[`PipeOp`].
+#' Only fields inherited from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].
 #'
 #' @section Methods:
-#' Methods inherited from [PipeOpTaskPreproc]/[PipeOp].
+#' Methods inherited from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].
 #'
 #' @family PipeOps
 #' @seealso https://mlr3book.mlr-org.com/list-pipeops.html
@@ -102,14 +104,14 @@
 #' # On newdata
 #' glrn$predict_newdata(task$data(cols = task$feature_names))
 PipeOpEOd = R6Class("PipeOpEOd",
-  inherit = PipeOp,
+  inherit = mlr3pipelines::PipeOp,
   public = list(
     #' @description
-    #' Creates a new instance of this [R6][R6::R6Class][PipeOp] R6 class.
+    #' Creates a new instance of this [R6::R6Class][mlr3pipelines::PipeOp] R6 class.
     #'
-    #' @param id `character` \cr
+    #' @param id character \cr
     #'   The PipeOps identifier in the PipeOps library.
-    #' @param param_vals `list` \cr
+    #' @param param_vals list \cr
     #'   The parameter values to be set. See `Parameters`.
     initialize = function(id = "EOd", param_vals = list()) {
       ps = ps(

R/PipeOpExplicitPta.R

@@ -16,15 +16,14 @@
 #' * `param_vals` (`list()`)
 #' 
 #' @section Input and Output Channels:
-#' Input and output channels are inherited from [PipeOpTaskPreproc]. Instead of a [Task][mlr3::Task], a
-#' [TaskClassif][mlr3::TaskClassif] is used as input and output during training and prediction.
+#' Input and output channels are inherited from [mlr3pipelines::PipeOpTaskPreproc]. Instead of a [mlr3::Task], a
+#' [mlr3::TaskClassif] is used as input and output during training and prediction.
 #'
-#' The output during training is the input [Task][mlr3::Task] with added weights column according
+#' The output during training is the input [mlr3::Task] with added weights column according
 #' to target class. The output during prediction is the unchanged input.
 #'
-#
 #' @section State:
-#' The `$state` is a named `list` with the `$state` elements inherited from [PipeOpTaskPreproc][mlr3pipelines::PipeOpTaskPreproc].
+#' The `$state` is a named `list` with the `$state` elements inherited from [mlr3pipelines::PipeOpTaskPreproc].
 #'
 #' @section Parameters:
 #' The PipeOp does not have any hyperparameters.
@@ -33,10 +32,10 @@
 #' Copies the existing pta column to a new column.
 #' 
 #' @section Fields:
-#' Only fields inherited from [PipeOpTaskPreproc]/[`PipeOp`].
+#' Only fields inherited from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].
 #'
 #' @section Methods:
-#' Methods inherited from [PipeOpTaskPreproc][mlr3pipelines::PipeOpTaskPreproc]/[PipeOp][mlr3pipelines::PipeOp].
+#' Methods inherited from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].
 #' 
 #' @family PipeOps
 #' @seealso https://mlr3book.mlr-org.com/list-pipeops.html
@@ -47,10 +46,10 @@
 #' epta = po("explicit_pta")
 #' new = epta$train(list(tsk("adult_train")))
 PipeOpExplicitPta = R6Class("PipeOpExplicitPta",
-  inherit = PipeOpTaskPreproc,
+  inherit = mlr3pipelines::PipeOpTaskPreproc,
   public = list(
     #' @description
-    #' Creates a new instance of this [R6][R6::R6Class][PipeOp] R6 class.
+    #' Creates a new instance of this [R6::R6Class][mlr3pipelines::PipeOpTaskPreproc] R6 class.
     #'
     #' @param id `character` \cr
     #'   The PipeOps identifier in the PipeOps library.

R/PipeOpReweighing.R

@@ -8,13 +8,13 @@
 #' Adjusts class balance and protected group balance in order to achieve fair(er) outcomes.
 #'
 #' @section PipeOpReweighingWeights:
-#' Adds a class weight column to the [Task][mlr3::Task] that different [`Learner`][mlr3::Learner]s
+#' Adds a class weight column to the [mlr3::Task] that different [mlr3::Learner]s
 #' may be using. In case initial weights are present, those are multiplied with new weights.
 #' Caution: Only fairness tasks are supported. Which means tasks need to have protected field.
 #' `tsk$col_roles$pta`.
 #'
 #' @section PipeOpReweighingOversampling:
-#' Oversamples a [Task][mlr3::Task] for more balanced ratios in subgroups and protected groups.
+#' Oversamples a [mlr3::Task] for more balanced ratios in subgroups and protected groups.
 #' Can be used if a learner does not support weights.
 #' Caution: Only fairness tasks are supported. Which means tasks need to have protected field.
 #' `tsk$col_roles$pta`.
@@ -30,31 +30,31 @@
 #' * `param_vals` (`list()`)
 #'
 #' @section Input and Output Channels:
-#' Input and output channels are inherited from [PipeOpTaskPreproc]. Instead of a [`Task`][mlr3::Task], a
-#' [TaskClassif][mlr3::TaskClassif] is used as input and output during training and prediction.
+#' Input and output channels are inherited from [mlr3pipelines::PipeOpTaskPreproc]. Instead of a [mlr3::Task], a
+#' [mlr3::TaskClassif] is used as input and output during training and prediction.
 #'
-#' The output during training is the input [Task][mlr3::Task] with added weights column according
+#' The output during training is the input [mlr3::Task] with added weights column according
 #' to target class. The output during prediction is the unchanged input.
 #'
 #' @section State:
-#' The `$state` is a named `list` with the `$state` elements inherited from [PipeOpTaskPreproc].
+#' The `$state` is a named `list` with the `$state` elements inherited from [mlr3pipelines::PipeOpTaskPreproc].
 #'
 #' @section Parameters:
 #'  * `alpha` (`numeric()`): A number between 0 (no debiasing) and 1 (full debiasing).
 #'
 #' @section Internals:
-#' Introduces, or overwrites, the "weights" column in the [Task][mlr3::Task].
-#' However, the [Learner][mlr3::Learner] method needs to
+#' Introduces, or overwrites, the "weights" column in the [mlr3::Task].
+#' However, the [mlr3::Learner] method needs to
 #' respect weights for this to have an effect.
 #'
 #' The newly introduced column is named `reweighing.WEIGHTS`; there will be a naming conflict if this
 #' column already exists and is *not* a weight column itself.
 #'
 #' @section Fields:
-#' Only fields inherited from [PipeOpTaskPreproc]/[`PipeOp`].
+#' Only fields inherited from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].
 #'
 #' @section Methods:
-#' Methods inherited from [PipeOpTaskPreproc]/[`PipeOp`].
+#' Methods inherited from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].
 #'
 #' @family PipeOps
 #' @seealso https://mlr3book.mlr-org.com/list-pipeops.html
@@ -76,7 +76,7 @@ PipeOpReweighingWeights = R6Class("PipeOpReweighingWeights",
   inherit = mlr3pipelines::PipeOpTaskPreproc,
   public = list(
     #' @description
-    #' Creates a new instance of this [R6][R6::R6Class][PipeOp] R6 class.
+    #' Creates a new instance of this [R6::R6Class][mlr3pipelines::PipeOpTaskPreproc] R6 class.
     #'
     #' @param id `character` \cr
     #'   The PipeOps identifier in the PipeOps library.

R/helpers.R

@@ -3,8 +3,8 @@
 #' @param prediction [mlr3::Prediction] A prediction
 #' @param base_measure [mlr3::Measure] The measure to compute in each group.
 #' @param task [mlr3::Task] the task prediction was made on.
-#' @param ... `any` passed on to respective measure.
-#' @return [numeric] Computed score
+#' @param ... any passed on to respective measure.
+#' @return numeric Computed score
 #'
 #' @noRd
 score_groupwise = function(prediction, base_measure, task, ...) {
@@ -22,7 +22,7 @@ score_groupwise = function(prediction, base_measure, task, ...) {
 #' Compute weights for PipeOpReweighing*
 #'
 #' @param task [mlr3::Task] the task
-#' @param alpha [numeric] Debiasing strength
+#' @param alpha numeric Debiasing strength
 #'
 #' @return [data.table] A data.table with counts and weights for each feature.
 #' @noRd

R/mlr_learners_fairness.R

@@ -2,7 +2,7 @@
 #' @name mlr_learners_fairness
 #'
 #' @section Predefined measures:
-#' \CRANpkg{mlr3fairness} comes with a set of predefined fairn learners listed below:
+#' \CRANpkg{mlr3fairness} comes with a set of predefined 'fair learners' listed below:
 #'
 #' `r tabular(mlr_learners_fairness)`
 #' 

R/mlr_measures_fairness.R

@@ -3,10 +3,10 @@
 #'
 #' @section Predefined measures:
 #' \CRANpkg{mlr3fairness} comes with a set of predefined fairness measures as listed below.
-#' For full flexibility, [MeasureFairness] can be used to construct classical
+#' For full flexibility, [mlr3fairness::MeasureFairness] can be used to construct classical
 #' group fairness measures based on a difference between a performance metrics across groups
 #' by combining a performance measure with an operation for measuring differences.
-#' Furthermore [MeasureSubgroup] can be used to measure performance in a given subgroup, or alternatively
+#' Furthermore [mlr3fairness::MeasureSubgroup] can be used to measure performance in a given subgroup, or alternatively
 #' groupwise_metrics(measure, task) to instantiate a measure for each subgroup in a [mlr3::Task].
 #'
 #' `r tabular(mlr_measures_fairness)`

R/mlr_pipeops_explicit_pta.R

@@ -1 +1 @@
-#' @format [R6::R6Class] object inheriting from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp]. 
+#' @format [R6::R6Class] object inheriting from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].

R/mlr_pipeops_reweighing.R

@@ -1 +1 @@
-#' @format [R6::R6Class] object inheriting from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp]. 
+#' @format [R6::R6Class] object inheriting from [mlr3pipelines::PipeOpTaskPreproc]/[mlr3pipelines::PipeOp].