diff --git a/hiclass/LocalClassifierPerLevel.py b/hiclass/LocalClassifierPerLevel.py
index 907e61cf..2420ac36 100644
--- a/hiclass/LocalClassifierPerLevel.py
+++ b/hiclass/LocalClassifierPerLevel.py
@@ -5,13 +5,13 @@
 """
 
 import hashlib
+import numpy as np
 import pickle
 from copy import deepcopy
-from os.path import exists
-
-import numpy as np
 from joblib import Parallel, delayed
+from os.path import exists
 from sklearn.base import BaseEstimator
+from sklearn.preprocessing import LabelEncoder
 from sklearn.utils.validation import check_array, check_is_fitted
 
 from hiclass.ConstantClassifier import ConstantClassifier
@@ -273,6 +273,9 @@ def _fit_classifier(self, level, separator):
             classifier = ConstantClassifier()
         if not self.bert:
             try:
+                label_encoder = LabelEncoder()
+                label_encoder.fit(y)
+                y = label_encoder.transform(y)
                 classifier.fit(X, y, sample_weight)
             except TypeError:
                 classifier.fit(X, y)
diff --git a/hiclass/LocalClassifierPerParentNode.py b/hiclass/LocalClassifierPerParentNode.py
index 47f77475..77d674a5 100644
--- a/hiclass/LocalClassifierPerParentNode.py
+++ b/hiclass/LocalClassifierPerParentNode.py
@@ -5,13 +5,13 @@
 """
 
 import hashlib
+import networkx as nx
+import numpy as np
 import pickle
 from copy import deepcopy
 from os.path import exists
-
-import networkx as nx
-import numpy as np
 from sklearn.base import BaseEstimator
+from sklearn.preprocessing import LabelEncoder
 from sklearn.utils.validation import check_array, check_is_fitted
 
 from hiclass.ConstantClassifier import ConstantClassifier
@@ -231,6 +231,9 @@ def _fit_classifier(self, node):
             classifier = ConstantClassifier()
         if not self.bert:
             try:
+                label_encoder = LabelEncoder()
+                label_encoder.fit(y)
+                y = label_encoder.transform(y)
                 classifier.fit(X, y, sample_weight)
             except TypeError:
                 classifier.fit(X, y)