diff --git a/summit/multiview_platform/monoview_classifiers/repeatboost.py b/summit/multiview_platform/monoview_classifiers/repeatboost.py
index cec9230cd1c4cbec76ecdae358068c3a65d45786..c7e605944dfcb9a6949a42f3304a6a81b15dbe33 100644
--- a/summit/multiview_platform/monoview_classifiers/repeatboost.py
+++ b/summit/multiview_platform/monoview_classifiers/repeatboost.py
@@ -23,7 +23,7 @@ class RepDT(DecisionTree):
     def fit(self, X, y, sample_weight=None, check_input=True):
         if sample_weight is not None:
             new_X, new_y = self.fake_repetitions(X, y, sample_weight,
-                                                 precision=5)
+                                                 precision=3)
         else:
             new_X = X
             new_y = y
diff --git a/summit/multiview_platform/monoview_classifiers/scm.py b/summit/multiview_platform/monoview_classifiers/scm.py
index 4ee442f138e3f37e80ec2969e49a4ddfb028ead3..375a08d6b076249d535915396dfb9e80dcdd0244 100644
--- a/summit/multiview_platform/monoview_classifiers/scm.py
+++ b/summit/multiview_platform/monoview_classifiers/scm.py
@@ -65,7 +65,7 @@ class SCM(scm, BaseMonoviewClassifier):
 
     def fit(self, X, y, tiebreaker=None, iteration_callback=None, sample_weight=None, **fit_params):
         if sample_weight is not None:
-            new_X, new_y = self.fake_repetitions(X, y, sample_weight, precision=5)
+            new_X, new_y = self.fake_repetitions(X, y, sample_weight, precision=3)
         else:
             new_X = X
             new_y = y