mlr-org · mb706 · Aug 15, 2025 · Aug 15, 2025 · Aug 15, 2025
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -51,7 +51,8 @@ Suggests:
     testthat (>= 3.0.0),
     xgboost (>= 1.6.0)
 Remotes:
-    mlr-org/mlr3
+    mlr-org/mlr3@common_baseclass,
+    mlr-org/mlr3misc@common_baseclass
 Config/testthat/edition: 3
 Encoding: UTF-8
 NeedsCompilation: no

diff --git a/R/LearnerClassifCVGlmnet.R b/R/LearnerClassifCVGlmnet.R
@@ -86,9 +86,7 @@ LearnerClassifCVGlmnet = R6Class("LearnerClassifCVGlmnet",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric"),
         properties = c("weights", "twoclass", "multiclass", "selected_features", "offset"),
-        packages = c("mlr3learners", "glmnet"),
-        label = "GLM with Elastic Net Regularization",
-        man = "mlr3learners::mlr_learners_classif.cv_glmnet"
+        packages = "glmnet"
       )
     },
 

diff --git a/R/LearnerClassifGlmnet.R b/R/LearnerClassifGlmnet.R
@@ -90,9 +90,7 @@ LearnerClassifGlmnet = R6Class("LearnerClassifGlmnet",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric"),
         properties = c("weights", "twoclass", "multiclass", "offset"),
-        packages = c("mlr3learners", "glmnet"),
-        label = "GLM with Elastic Net Regularization",
-        man = "mlr3learners::mlr_learners_classif.glmnet"
+        packages = "glmnet"
       )
     },
 

diff --git a/R/LearnerClassifKKNN.R b/R/LearnerClassifKKNN.R
@@ -44,9 +44,7 @@ LearnerClassifKKNN = R6Class("LearnerClassifKKNN",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric", "factor", "ordered"),
         properties = c("twoclass", "multiclass"),
-        packages = c("mlr3learners", "kknn"),
-        label = "k-Nearest-Neighbor",
-        man = "mlr3learners::mlr_learners_classif.kknn"
+        packages = "kknn"
       )
     }
   ),

diff --git a/R/LearnerClassifLDA.R b/R/LearnerClassifLDA.R
@@ -45,9 +45,7 @@ LearnerClassifLDA = R6Class("LearnerClassifLDA",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric", "factor", "ordered"),
         properties = c("twoclass", "multiclass"),
-        packages = c("mlr3learners", "MASS"),
-        label = "Linear Discriminant Analysis",
-        man = "mlr3learners::mlr_learners_classif.lda"
+        packages = "MASS"
       )
     }
   ),

diff --git a/R/LearnerClassifLogReg.R b/R/LearnerClassifLogReg.R
@@ -63,9 +63,7 @@ LearnerClassifLogReg = R6Class("LearnerClassifLogReg",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric", "character", "factor", "ordered"),
         properties = c("weights", "twoclass", "offset"),
-        packages = c("mlr3learners", "stats"),
-        label = "Logistic Regression",
-        man = "mlr3learners::mlr_learners_classif.log_reg"
+        packages = "stats"
       )
     }
   ),

diff --git a/R/LearnerClassifMultinom.R b/R/LearnerClassifMultinom.R
@@ -47,9 +47,7 @@ LearnerClassifMultinom = R6Class("LearnerClassifMultinom",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric", "factor"),
         properties = c("weights", "twoclass", "multiclass"),
-        packages = c("mlr3learners", "nnet"),
-        label = "Multinomial Log-Linear Model",
-        man = "mlr3learners::mlr_learners_classif.multinom"
+        packages = "nnet"
       )
     }
   ),

diff --git a/R/LearnerClassifNaiveBayes.R b/R/LearnerClassifNaiveBayes.R
@@ -32,9 +32,7 @@ LearnerClassifNaiveBayes = R6Class("LearnerClassifNaiveBayes",
         predict_types = c("response", "prob"),
         properties = c("twoclass", "multiclass"),
         feature_types = c("logical", "integer", "numeric", "factor"),
-        packages = c("mlr3learners", "e1071"),
-        label = "Naive Bayes",
-        man = "mlr3learners::mlr_learners_classif.naive_bayes"
+        packages = "e1071"
       )
     }
   ),

diff --git a/R/LearnerClassifNnet.R b/R/LearnerClassifNnet.R
@@ -56,13 +56,11 @@ LearnerClassifNnet = R6Class("LearnerClassifNnet",
 
       super$initialize(
         id = "classif.nnet",
-        packages = c("mlr3learners", "nnet"),
+        packages = "nnet",
         feature_types = c("logical", "numeric", "factor", "ordered", "integer"),
         predict_types = c("prob", "response"),
         param_set = ps,
-        properties = c("twoclass", "multiclass", "weights"),
-        label = "Single Layer Neural Network",
-        man = "mlr3learners::mlr_learners_classif.nnet"
+        properties = c("twoclass", "multiclass", "weights")
       )
     }
   ),

diff --git a/R/LearnerClassifQDA.R b/R/LearnerClassifQDA.R
@@ -43,9 +43,7 @@ LearnerClassifQDA = R6Class("LearnerClassifQDA",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric", "factor", "ordered"),
         properties = c("twoclass", "multiclass"),
-        packages = c("mlr3learners", "MASS"),
-        label = "Quadratic Discriminant Analysis",
-        man = "mlr3learners::mlr_learners_classif.qda"
+        packages = "MASS"
       )
     }
   ),

diff --git a/R/LearnerClassifRanger.R b/R/LearnerClassifRanger.R
@@ -84,9 +84,7 @@ LearnerClassifRanger = R6Class("LearnerClassifRanger",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric", "character", "factor", "ordered"),
         properties = c("weights", "twoclass", "multiclass", "importance", "oob_error", "hotstart_backward", "missings", "selected_features"),
-        packages = c("mlr3learners", "ranger"),
-        label = "Random Forest",
-        man = "mlr3learners::mlr_learners_classif.ranger"
+        packages = "ranger"
       )
     },
 

diff --git a/R/LearnerClassifSVM.R b/R/LearnerClassifSVM.R
@@ -48,9 +48,7 @@ LearnerClassifSVM = R6Class("LearnerClassifSVM",
         predict_types = c("response", "prob"),
         feature_types = c("logical", "integer", "numeric"),
         properties = c("twoclass", "multiclass"),
-        packages = c("mlr3learners", "e1071"),
-        label = "Support Vector Machine",
-        man = "mlr3learners::mlr_learners_classif.svm"
+        packages = "e1071"
       )
     }
   ),

diff --git a/R/LearnerClassifXgboost.R b/R/LearnerClassifXgboost.R
@@ -162,9 +162,7 @@ LearnerClassifXgboost = R6Class("LearnerClassifXgboost",
         param_set = ps,
         feature_types = c("logical", "integer", "numeric"),
         properties = c("weights", "missings", "twoclass", "multiclass", "importance", "hotstart_forward", "internal_tuning", "validation", "offset"),
-        packages = c("mlr3learners", "xgboost"),
-        label = "Extreme Gradient Boosting",
-        man = "mlr3learners::mlr_learners_classif.xgboost"
+        packages = "xgboost"
       )
     },
 

diff --git a/R/LearnerRegrCVGlmnet.R b/R/LearnerRegrCVGlmnet.R
@@ -80,9 +80,7 @@ LearnerRegrCVGlmnet = R6Class("LearnerRegrCVGlmnet",
         param_set = ps,
         feature_types = c("logical", "integer", "numeric"),
         properties = c("weights", "selected_features", "offset"),
-        packages = c("mlr3learners", "glmnet"),
-        label = "GLM with Elastic Net Regularization",
-        man = "mlr3learners::mlr_learners_regr.cv_glmnet"
+        packages = "glmnet"
       )
     },
 

diff --git a/R/LearnerRegrGlmnet.R b/R/LearnerRegrGlmnet.R
@@ -78,9 +78,7 @@ LearnerRegrGlmnet = R6Class("LearnerRegrGlmnet",
         param_set = ps,
         feature_types = c("logical", "integer", "numeric"),
         properties = c("weights", "offset"),
-        packages = c("mlr3learners", "glmnet"),
-        label = "GLM with Elastic Net Regularization",
-        man = "mlr3learners::mlr_learners_regr.glmnet"
+        packages = "glmnet"
       )
     },
 

diff --git a/R/LearnerRegrKKNN.R b/R/LearnerRegrKKNN.R
@@ -43,9 +43,7 @@ LearnerRegrKKNN = R6Class("LearnerRegrKKNN",
         id = "regr.kknn",
         param_set = ps,
         feature_types = c("logical", "integer", "numeric", "factor", "ordered"),
-        packages = c("mlr3learners", "kknn"),
-        label = "k-Nearest-Neighbor",
-        man = "mlr3learners::mlr_learners_regr.kknn"
+        packages = "kknn"
       )
     }
   ),

diff --git a/R/LearnerRegrKM.R b/R/LearnerRegrKM.R
@@ -67,9 +67,7 @@ LearnerRegrKM = R6Class("LearnerRegrKM",
         param_set = ps,
         predict_types = c("response", "se"),
         feature_types = c("logical", "integer", "numeric"),
-        packages = c("mlr3learners", "DiceKriging"),
-        label = "Kriging",
-        man = "mlr3learners::mlr_learners_regr.km"
+        packages = "DiceKriging"
       )
     }
   ),

diff --git a/R/LearnerRegrLM.R b/R/LearnerRegrLM.R
@@ -54,9 +54,7 @@ LearnerRegrLM = R6Class("LearnerRegrLM",
         predict_types = c("response", "se"),
         feature_types = c("logical", "integer", "numeric", "factor", "character"),
         properties = c("weights", "offset"),
-        packages = c("mlr3learners", "stats"),
-        label = "Linear Model",
-        man = "mlr3learners::mlr_learners_regr.lm"
+        packages = "stats"
       )
     }
   ),

diff --git a/R/LearnerRegrNnet.R b/R/LearnerRegrNnet.R
@@ -56,13 +56,11 @@ LearnerRegrNnet = R6Class("LearnerRegrNnet",
 
       super$initialize(
         id = "regr.nnet",
-        packages = c("mlr3learners", "nnet"),
+        packages = "nnet",
         feature_types = c("logical", "numeric", "factor", "ordered", "integer"),
         predict_types = "response",
         param_set = ps,
-        properties = "weights",
-        label = "Single Layer Neural Network",
-        man = "mlr3learners::mlr_learners_regr.nnet"
+        properties = "weights"
       )
     }
   ),

diff --git a/R/LearnerRegrRanger.R b/R/LearnerRegrRanger.R
@@ -66,9 +66,7 @@ LearnerRegrRanger = R6Class("LearnerRegrRanger",
         predict_types = c("response", "se", "quantiles"),
         feature_types = c("logical", "integer", "numeric", "character", "factor", "ordered"),
         properties = c("weights", "importance", "oob_error", "hotstart_backward", "missings", "selected_features"),
-        packages = c("mlr3learners", "ranger"),
-        label = "Random Forest",
-        man = "mlr3learners::mlr_learners_regr.ranger"
+        packages = "ranger"
       )
     },
 

diff --git a/R/LearnerRegrSVM.R b/R/LearnerRegrSVM.R
@@ -43,9 +43,7 @@ LearnerRegrSVM = R6Class("LearnerRegrSVM",
         id = "regr.svm",
         param_set = ps,
         feature_types = c("logical", "integer", "numeric"),
-        packages = c("mlr3learners", "e1071"),
-        label = "Support Vector Machine",
-        man = "mlr3learners::mlr_learners_regr.svm"
+        packages = "e1071"
       )
     }
   ),

diff --git a/R/LearnerRegrXgboost.R b/R/LearnerRegrXgboost.R
@@ -142,9 +142,7 @@ LearnerRegrXgboost = R6Class("LearnerRegrXgboost",
         param_set = ps,
         feature_types = c("logical", "integer", "numeric"),
         properties = c("weights", "missings", "importance", "hotstart_forward", "internal_tuning", "validation", "offset"),
-        packages = c("mlr3learners", "xgboost"),
-        label = "Extreme Gradient Boosting",
-        man = "mlr3learners::mlr_learners_regr.xgboost"
+        packages = "xgboost"
       )
     },
 

diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R
@@ -1,11 +1,12 @@
 old_opts = options(
   warnPartialMatchArgs = TRUE,
   warnPartialMatchAttr = TRUE,
-  warnPartialMatchDollar = TRUE
+  warnPartialMatchDollar = TRUE,
+  mlr3.on_deprecated_mlr3component = "error"
 )
 
 # https://github.com/HenrikBengtsson/Wishlist-for-R/issues/88
-old_opts = lapply(old_opts, function(x) if (is.null(x)) FALSE else x)
+old_opts[1:3] = lapply(old_opts[1:3], function(x) if (is.null(x)) FALSE else x)
 
 lg = lgr::get_logger("mlr3")
 old_threshold = lg$threshold