diff --git a/LocalStack/experiments.py b/LocalStack/experiments.py
index 6b083a5..d4c9f4a 100644
--- a/LocalStack/experiments.py
+++ b/LocalStack/experiments.py
@@ -3,7 +3,7 @@ from time import time
 import numpy as np
 from sklearn.linear_model import LogisticRegression
 import quapy as qp
-from KDEy.kdey_devel import KDEyMLauto, KDEyMLauto2, KDEyMLred
+#from KDEy.kdey_devel import KDEyMLauto, KDEyMLauto2, KDEyMLred
 from LocalStack.method import LocalStackingQuantification, LocalStackingQuantification2
 from quapy.method.aggregative import PACC, EMQ, KDEyML
 from quapy.model_selection import GridSearchQ
@@ -123,4 +123,4 @@ if __name__ == '__main__':
                 csv.write(f'{method_name}\t{dataset}\t{means["mae"]:.5f}\t{means["mrae"]:.5f}\t{means["kld"]:.5f}\t{means["tr_time"]:.3f}\t{means["te_time"]:.3f}\n')
                 csv.flush()
 
-    show_results(global_result_path)
\ No newline at end of file
+    show_results(global_result_path)
diff --git a/LocalStack/method.py b/LocalStack/method.py
index 157c73d..ffa7e74 100644
--- a/LocalStack/method.py
+++ b/LocalStack/method.py
@@ -3,7 +3,7 @@ import quapy as qp
 from sklearn.multioutput import MultiOutputRegressor
 from sklearn.svm import SVR
 
-from data import LabelledCollection
+from quapy.data import LabelledCollection
 from quapy.method.base import BaseQuantifier
 from quapy.method.aggregative import AggregativeSoftQuantifier
 
@@ -109,4 +109,4 @@ class LocalStackingQuantification2(BaseQuantifier):
         corrected_prev = reg.predict([pred_prevs])[0]
 
         corrected_prev = self.normalize(corrected_prev)
-        return corrected_prev
\ No newline at end of file
+        return corrected_prev