diff --git a/pyFTS/partitioners/Entropy.py b/pyFTS/partitioners/Entropy.py
index 914c70f..0bf8e1e 100644
--- a/pyFTS/partitioners/Entropy.py
+++ b/pyFTS/partitioners/Entropy.py
@@ -40,7 +40,7 @@ def informationGain(data, thres1, thres2):
 
 def bestSplit(data, npart):
     if len(data) < 2:
-        return None
+        return []
     count = 1
     ndata = list(set(np.array(data).flatten()))
     ndata.sort()
diff --git a/pyFTS/tests/general.py b/pyFTS/tests/general.py
index 1aac53b..ebd7038 100644
--- a/pyFTS/tests/general.py
+++ b/pyFTS/tests/general.py
@@ -17,36 +17,13 @@ from pyFTS.common import Transformations
 tdiff = Transformations.Differential(1)
 
 
-from pyFTS.data import TAIEX, SP500, NASDAQ
+from pyFTS.data import TAIEX, SP500, NASDAQ, Malaysia
 
-dataset = TAIEX.get_data()
+dataset = Malaysia.get_data('temperature')[:1000]
 
-from pyFTS.models.incremental import Retrainer
+p = Entropy.EntropyPartitioner(data=dataset, npart=19)
 
-from pyFTS.models.incremental import Retrainer
-from pyFTS.benchmarks import benchmarks as bchmk
-
-models = []
-for method in bchmk.get_point_methods():
-  model = Retrainer.Retrainer(partitioner_params = {'npart': 30},
-                    fts_method=method,
-                    window_length = 500, batch_size = 100)
-  models.append(model)
-
-#model.predict(dataset)
-
-from pyFTS.partitioners import Grid, Util as pUtil
-from pyFTS.benchmarks import benchmarks as bchmk, naive
-
-tag = 'benchmarks_retrainer'
-
-bchmk.sliding_window_benchmarks(dataset, 2000, train=.1, inc=0.1,
-                              models=[model],
-                              build_methods = False,
-                              benchmark_models=False,
-                              partitions=[35],
-                              progress=False, type='point',
-                              file="nsfts_benchmarks.db", dataset='teste', tag=tag)
+print(p)
 
 '''
 #dataset = SP500.get_data()[11500:16000]