update docs

R/mlr_learner.R

@@ -40,13 +40,10 @@ ichecker = function(x) {
   }
 }
 
-#' @title Component-wise boosting learner
-#'
-#' @name mlr_learners.compboost
+#' @title Component-wise gradient boosting learner
 #'
 #' @description
-#' A [Learner] for a component-wise boosting model implemented in [compboost::Compboost]
-#' in package \CRANpkg{compboost}.
+#' A [Learner] for a component-wise boosting model implemented in [compboost::Compboost].
 #'
 #' @importFrom mlr3 mlr_learners Learner
 LearnerCompboost = R6::R6Class("LearnerCompboost", inherit = Learner,
@@ -237,13 +234,10 @@ LearnerCompboost = R6::R6Class("LearnerCompboost", inherit = Learner,
   )
 )
 
-#' @title Classification component-wise boosting learner
-#'
-#' @name mlr_learners_classif.compboost
+#' @title Component-wise gradient boosting classification learner
 #'
 #' @description
-#' A [Learner] for a component-wise boosting model implemented in [compboost::Compboost]
-#' in package \CRANpkg{compboost}.
+#' A [Learner] for a component-wise boosting model implemented in [compboost::Compboost].
 #'
 #' @examples
 #' l = lrn("classif.compboost", baselearner = "components",
@@ -262,13 +256,10 @@ LearnerClassifCompboost = R6::R6Class("LearnerClassifCompboost", inherit = Learn
   )
 )
 
-#' @title Regression component-wise boosting learner
-#'
-#' @name mlr_learners_regr.compboost
+#' @title Component-wise gradient boosting regression learner
 #'
 #' @description
-#' A [Learner] for a component-wise boosting model implemented in [compboost::Compboost]
-#' in package \CRANpkg{compboost}.
+#' A [Learner] for a component-wise boosting model implemented in [compboost::Compboost].
 #'
 #' @examples
 #' l = lrn("regr.compboost", baselearner = "linear", iterations = 50)

R/plot_tensor.R

@@ -21,10 +21,10 @@
 #' cboost = Compboost$new(data = iris, target = "Petal.Length",
 #'   loss = LossQuadratic$new(), learning_rate = 0.2)
 #'
-#' cboost$addTensor("Sepal.Width", "Sepal.Length", df1 = 4, df2 = 4)
-#' cboost$addTensor("Sepal.Width", "Species", df1 = 4, df2 = 2)
+#' cboost$addTensor("Sepal.Width", "Sepal.Length", df1 = 4, df2 = 4, n_knots = 10)
+#' cboost$addTensor("Sepal.Width", "Species", df1 = 4, df2 = 2, n_knots = 10)
 #'
-#' cboost$train(50L)
+#' cboost$train(40L)
 #'
 #' plotTensor(cboost, "Sepal.Width_Species_tensor")
 #' plotTensor(cboost, "Sepal.Width_Sepal.Length_tensor")
@@ -44,7 +44,7 @@ plotTensor = function(cboost, tname, npoints = 100L, nbins = 15L) {
   if (! checkmate::testChoice(x = tname, choices = blsel)) {
     stop("Tensor base learner '", tname, "' was not selected. The selected base learner are {",
       paste(paste0("'", blsel, "'"), collapse = ","), "}. Maybe you misspelled the base learner",
-      "or did not train long enough.")
+      " or did not train long enough.")
   }
 
   checkmate::assertIntegerish(x = npoints, len = 1L, lower = 10L)