diff --git a/R/LearnerClustAffinityPropagation.R b/R/LearnerClustAffinityPropagation.R
index 4c577573..a9a5019c 100644
--- a/R/LearnerClustAffinityPropagation.R
+++ b/R/LearnerClustAffinityPropagation.R
@@ -63,6 +63,7 @@ LearnerClustAP = R6Class("LearnerClustAP",
 
       return(m)
     },
+
     .predict = function(task) {
       sim_func = self$param_set$values$s
       exemplar_data = attributes(self$model)$exemplar_data
diff --git a/R/LearnerClustAgnes.R b/R/LearnerClustAgnes.R
index d30e0fd4..6b2fa93b 100644
--- a/R/LearnerClustAgnes.R
+++ b/R/LearnerClustAgnes.R
@@ -70,6 +70,7 @@ LearnerClustAgnes = R6Class("LearnerClustAgnes",
 
       return(m)
     },
+
     .predict = function(task) {
       if (self$param_set$values$k > task$nrow) {
         stopf("`k` needs to be between 1 and %i", task$nrow)
diff --git a/R/LearnerClustCMeans.R b/R/LearnerClustCMeans.R
index 4294b482..ed688fb8 100644
--- a/R/LearnerClustCMeans.R
+++ b/R/LearnerClustCMeans.R
@@ -70,6 +70,7 @@ LearnerClustCMeans = R6Class("LearnerClustCMeans",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = unclass(cl_predict(self$model, newdata = task$data(), type = "class_ids"))
       prob = unclass(cl_predict(self$model, newdata = task$data(), type = "memberships"))
diff --git a/R/LearnerClustCobweb.R b/R/LearnerClustCobweb.R
index ade38ca1..9181abc4 100644
--- a/R/LearnerClustCobweb.R
+++ b/R/LearnerClustCobweb.R
@@ -49,6 +49,7 @@ LearnerClustCobweb = R6Class("LearnerClustCobweb",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = predict(self$model, newdata = task$data(), type = "class") + 1L
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustDBSCAN.R b/R/LearnerClustDBSCAN.R
index 7330b7a9..4e592d72 100644
--- a/R/LearnerClustDBSCAN.R
+++ b/R/LearnerClustDBSCAN.R
@@ -62,6 +62,7 @@ LearnerClustDBSCAN = R6Class("LearnerClustDBSCAN",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = predict(self$model, newdata = task$data(), self$model$data)
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustDBSCANfpc.R b/R/LearnerClustDBSCANfpc.R
index 91276740..a62827e8 100644
--- a/R/LearnerClustDBSCANfpc.R
+++ b/R/LearnerClustDBSCANfpc.R
@@ -70,6 +70,7 @@ LearnerClustDBSCANfpc = R6Class("LearnerClustDBSCANfpc",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = as.integer(predict(self$model, data = self$model$data, newdata = task$data()))
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustDiana.R b/R/LearnerClustDiana.R
index d9abdfd5..66d5e225 100644
--- a/R/LearnerClustDiana.R
+++ b/R/LearnerClustDiana.R
@@ -51,6 +51,7 @@ LearnerClustDiana = R6Class("LearnerClustDiana",
 
       return(m)
     },
+
     .predict = function(task) {
       if (test_true(self$param_set$values$k > task$nrow)) {
         stopf("`k` needs to be between 1 and %s", task$nrow)
diff --git a/R/LearnerClustEM.R b/R/LearnerClustEM.R
index 7d00bb9e..f6b23d0a 100644
--- a/R/LearnerClustEM.R
+++ b/R/LearnerClustEM.R
@@ -60,6 +60,7 @@ LearnerClustEM = R6Class("LearnerClustEM",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = predict(self$model, newdata = task$data(), type = "class") + 1L
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustFanny.R b/R/LearnerClustFanny.R
index cc1756c6..1d382450 100644
--- a/R/LearnerClustFanny.R
+++ b/R/LearnerClustFanny.R
@@ -57,6 +57,7 @@ LearnerClustFanny = R6Class("LearnerClustFanny",
 
       return(m)
     },
+
     .predict = function(task) {
       warn_prediction_useless(self$id)
 
diff --git a/R/LearnerClustFarthestFirst.R b/R/LearnerClustFarthestFirst.R
index 8cf3da58..de8677cd 100644
--- a/R/LearnerClustFarthestFirst.R
+++ b/R/LearnerClustFarthestFirst.R
@@ -59,6 +59,7 @@ LearnerClustFarthestFirst = R6Class("LearnerClustFF",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = predict(self$model, newdata = task$data(), type = "class") + 1L
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustFeatureless.R b/R/LearnerClustFeatureless.R
index d477c8f9..b6774569 100644
--- a/R/LearnerClustFeatureless.R
+++ b/R/LearnerClustFeatureless.R
@@ -55,6 +55,7 @@ LearnerClustFeatureless = R6Class("LearnerClustFeatureless",
         "clust.featureless_model"
       )
     },
+
     .predict = function(task) {
       pv = self$param_set$get_values(tags = "predict")
       n = task$nrow
diff --git a/R/LearnerClustHclust.R b/R/LearnerClustHclust.R
index de31a14c..4c2361d7 100644
--- a/R/LearnerClustHclust.R
+++ b/R/LearnerClustHclust.R
@@ -69,6 +69,7 @@ LearnerClustHclust = R6Class("LearnerClustHclust",
 
       return(m)
     },
+
     .predict = function(task) {
       if (self$param_set$values$k > task$nrow) {
         stopf("`k` needs to be between 1 and %i", task$nrow)
diff --git a/R/LearnerClustKKMeans.R b/R/LearnerClustKKMeans.R
index 5caaf8e7..a5cc9ca5 100644
--- a/R/LearnerClustKKMeans.R
+++ b/R/LearnerClustKKMeans.R
@@ -72,6 +72,7 @@ LearnerClustKKMeans = R6Class("LearnerClustKKMeans",
       }
       return(m)
     },
+
     .predict = function(task) {
       # all of predict is taken from mlr2
 
diff --git a/R/LearnerClustKMeans.R b/R/LearnerClustKMeans.R
index e472cfca..3745f3bb 100644
--- a/R/LearnerClustKMeans.R
+++ b/R/LearnerClustKMeans.R
@@ -47,6 +47,7 @@ LearnerClustKMeans = R6Class("LearnerClustKMeans",
       )
     }
   ),
+
   private = list(
     .train = function(task) {
       if ("nstart" %in% names(self$param_set$values)) {
@@ -65,6 +66,7 @@ LearnerClustKMeans = R6Class("LearnerClustKMeans",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = unclass(cl_predict(self$model, newdata = task$data(), type = "class_ids"))
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustMclust.R b/R/LearnerClustMclust.R
index cb8c54e7..4ba26380 100644
--- a/R/LearnerClustMclust.R
+++ b/R/LearnerClustMclust.R
@@ -53,6 +53,7 @@ LearnerClustMclust = R6Class("LearnerClustMclust",
 
       return(m)
     },
+
     .predict = function(task) {
       predictions = predict(self$model, newdata = task$data())
       partition = as.integer(predictions$classification)
diff --git a/R/LearnerClustMeanShift.R b/R/LearnerClustMeanShift.R
index 56425f9b..f8e1e454 100644
--- a/R/LearnerClustMeanShift.R
+++ b/R/LearnerClustMeanShift.R
@@ -62,6 +62,7 @@ LearnerClustMeanShift = R6Class("LearnerClustMeanShift",
 
       return(m)
     },
+
     .predict = function(task) {
       warn_prediction_useless(self$id)
       partition = as.integer(self$model$cluster.label)
diff --git a/R/LearnerClustMiniBatchKMeans.R b/R/LearnerClustMiniBatchKMeans.R
index f9d8a953..a7afff39 100644
--- a/R/LearnerClustMiniBatchKMeans.R
+++ b/R/LearnerClustMiniBatchKMeans.R
@@ -78,6 +78,7 @@ LearnerClustMiniBatchKMeans = R6Class("LearnerClustMiniBatchKMeans",
 
       return(m)
     },
+
     .predict = function(task) {
       if (self$predict_type == "partition") {
         partition = unclass(ClusterR::predict_MBatchKMeans(
diff --git a/R/LearnerClustPAM.R b/R/LearnerClustPAM.R
index 3e6568bc..2fef1281 100644
--- a/R/LearnerClustPAM.R
+++ b/R/LearnerClustPAM.R
@@ -73,6 +73,7 @@ LearnerClustPAM = R6Class("LearnerClustPAM",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = unclass(cl_predict(self$model, newdata = task$data(), type = "class_ids"))
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustSimpleKMeans.R b/R/LearnerClustSimpleKMeans.R
index c9b007fd..a6d2426a 100644
--- a/R/LearnerClustSimpleKMeans.R
+++ b/R/LearnerClustSimpleKMeans.R
@@ -73,6 +73,7 @@ LearnerClustSimpleKMeans = R6Class("LearnerClustSimpleKMeans",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = predict(self$model, newdata = task$data(), type = "class") + 1L
       PredictionClust$new(task = task, partition = partition)
diff --git a/R/LearnerClustXMeans.R b/R/LearnerClustXMeans.R
index aa921804..53a23408 100644
--- a/R/LearnerClustXMeans.R
+++ b/R/LearnerClustXMeans.R
@@ -63,6 +63,7 @@ LearnerClustXMeans = R6Class("LearnerClustXMeans",
 
       return(m)
     },
+
     .predict = function(task) {
       partition = predict(self$model, newdata = task$data(), type = "class") + 1L
       PredictionClust$new(task = task, partition = partition)