diff --git a/pyFTS/common/FuzzySet.py b/pyFTS/common/FuzzySet.py
index 58301f1..1f04a52 100644
--- a/pyFTS/common/FuzzySet.py
+++ b/pyFTS/common/FuzzySet.py
@@ -72,9 +72,9 @@ def __binary_search(x, fuzzy_sets, ordered_sets):
     :param ordered_sets: a list with the fuzzy sets names ordered by their centroids.
     :return: A list with the best fuzzy sets that may contain x
     """
-    max_len = len(fuzzy_sets)
+    max_len = len(fuzzy_sets) - 1
     first = 0
-    last = max_len-1
+    last = max_len
 
     while first <= last:
         midpoint = (first + last) // 2
@@ -85,6 +85,10 @@ def __binary_search(x, fuzzy_sets, ordered_sets):
 
         if fuzzy_sets[fs1].centroid <= x <= fuzzy_sets[fs2].centroid:
             return (midpoint-1, midpoint, midpoint+1)
+        elif midpoint <= 1:
+            return [0]
+        elif midpoint >= max_len:
+            return [max_len]
         else:
             if x < fuzzy_sets[fs].centroid:
                 last = midpoint - 1
@@ -92,6 +96,7 @@ def __binary_search(x, fuzzy_sets, ordered_sets):
                 first = midpoint + 1
 
 
+
 def fuzzyfy(data, partitioner, **kwargs):
     """
     A general method for fuzzyfication.
diff --git a/pyFTS/tests/general.py b/pyFTS/tests/general.py
index ad5987a..f6db17a 100644
--- a/pyFTS/tests/general.py
+++ b/pyFTS/tests/general.py
@@ -19,20 +19,21 @@ tdiff = Transformations.Differential(1)
 from pyFTS.data import TAIEX, SP500, NASDAQ
 
 dataset = TAIEX.get_data()
-
-partitioner = Grid.GridPartitioner(data=dataset, npart=30)
+'''
+partitioner = Grid.GridPartitioner(data=dataset[:800], npart=3, transformation=tdiff)
 
 model = chen.ConventionalFTS(partitioner=partitioner)
+model.append_transformation(tdiff)
 
-model.fit(dataset)
+model.fit([0, 90.00])
 
 print(model)
-
+'''
 #dataset = SP500.get_data()[11500:16000]
 #dataset = NASDAQ.get_data()
 #print(len(dataset))
 
-'''
+
 bchmk.sliding_window_benchmarks(dataset, 1000, train=0.8, inc=0.2,
                                 methods=[chen.ConventionalFTS], #[pwfts.ProbabilisticWeightedFTS],
                                 benchmark_models=False,
@@ -47,16 +48,16 @@ bchmk.sliding_window_benchmarks(dataset, 1000, train=0.8, inc=0.2,
 
 
 bchmk.sliding_window_benchmarks(dataset, 1000, train=0.8, inc=0.2,
-                                methods=[hofts.HighOrderFTS],  # [pwfts.ProbabilisticWeightedFTS],
+                                methods=[chen.ConventionalFTS],  # [pwfts.ProbabilisticWeightedFTS],
                                 benchmark_models=False,
                                 transformations=[tdiff],
-                                orders=[1, 2, 3],
-                                partitions=np.arange(3, 25, 2),
+                                #orders=[1, 2, 3],
+                                partitions=np.arange(3, 30, 1),
                                 progress=False, type="point",
                                 #steps_ahead=[1,2,4,6,8,10],
-                                distributed=True, nodes=['192.168.0.110', '192.168.0.107', '192.168.0.106'],
+                                distributed=False, nodes=['192.168.0.110', '192.168.0.107', '192.168.0.106'],
                                 file="benchmarks.db", dataset="NASDAQ", tag="comparisons")
-
+'''
 '''
 '''
 from pyFTS.partitioners import Grid, Util as pUtil