diff --git a/chen.py b/chen.py
index 2781b48..0efe40b 100644
--- a/chen.py
+++ b/chen.py
@@ -22,7 +22,7 @@ class ConventionalFTS(fts.FTS):
 	def __init__(self,name):
 		super(ConventionalFTS, self).__init__(1,name)
         
-	def defuzzy(self,data):
+	def forecast(self,data):
         
 		actual = self.fuzzy(data)
         
@@ -40,7 +40,7 @@ class ConventionalFTS(fts.FTS):
 
 		return denom/count
         
-	def learn(self, data, sets):
+	def train(self, data, sets):
 		last = {"fuzzyset":"", "membership":0.0}
 		actual = {"fuzzyset":"", "membership":0.0}
 		
diff --git a/fts.py b/fts.py
index c4cd802..7def69a 100644
--- a/fts.py
+++ b/fts.py
@@ -18,17 +18,17 @@ class FTS:
 
 		return best
 
-	def defuzzy(self,data):
+	def forecast(self,data):
 		pass
 
-	def learn(self, data, sets):
+	def train(self, data, sets):
 		pass  
 
 	def predict(self,data):
-		return self.defuzzy(data)
+		return self.forecast(data)
 
 	def predictDiff(self,data,t):
-		return data[t] + self.defuzzy(data[t-1]-data[t])
+		return data[t] + self.forecast(data[t-1]-data[t])
 
 	def __str__(self):
 		tmp = self.name + ":\n"
diff --git a/hwang.py b/hwang.py
index 4ae777b..42dcfea 100644
--- a/hwang.py
+++ b/hwang.py
@@ -5,7 +5,7 @@ class HighOrderFTS(fts.FTS):
 	def __init__(self,order,name):
 		super(HighOrderFTS, self).__init__(order,name)
         
-	def defuzzy(self,data,t):
+	def forecast(self,data,t):
 		cn = np.array([0.0 for k in range(len(self.sets))])
 		ow = np.array([[0.0 for k in range(len(self.sets))] for z in range(self.order-1)])
 		rn = np.array([[0.0 for k in range(len(self.sets))] for z in range(self.order-1)])
@@ -27,11 +27,11 @@ class HighOrderFTS(fts.FTS):
 		return out / count
 
 
-	def learn(self, data, sets):
+	def train(self, data, sets):
 		self.sets = sets
     
 	def predict(self,data,t):
-		return self.defuzzy(data,t)
+		return self.forecast(data,t)
 
 	def predictDiff(self,data,t):
-		return data[t] + self.defuzzy(common.differential(data),t)
+		return data[t] + self.forecast(common.differential(data),t)
diff --git a/ismailefendi.py b/ismailefendi.py
index 7027e37..e3fde55 100644
--- a/ismailefendi.py
+++ b/ismailefendi.py
@@ -31,7 +31,7 @@ class ImprovedWeightedFTS(fts.FTS):
 	def __init__(self,name):
 		super(ImprovedWeightedFTS, self).__init__(1,name)
         
-	def defuzzy(self,data):
+	def forecast(self,data):
 		actual = self.fuzzy(data)
 		if actual["fuzzyset"] not in self.flrgs:
 			return self.sets[actual["fuzzyset"]].centroid
@@ -39,7 +39,7 @@ class ImprovedWeightedFTS(fts.FTS):
 		mi = np.array([self.sets[s].centroid for s in flrg.RHS.keys()])
 		return mi.dot( flrg.weights() )
         
-	def learn(self, data, sets):
+	def train(self, data, sets):
 		last = {"fuzzyset":"", "membership":0.0}
 		actual = {"fuzzyset":"", "membership":0.0}
 		
diff --git a/sadaei.py b/sadaei.py
index 5676978..60b4d1f 100644
--- a/sadaei.py
+++ b/sadaei.py
@@ -34,7 +34,7 @@ class ExponentialyWeightedFTS(fts.FTS):
 	def __init__(self,name):
 		super(ExponentialyWeightedFTS, self).__init__(1,name)
         
-	def defuzzy(self,data):
+	def forecast(self,data):
         
 		actual = self.fuzzy(data)
         
@@ -47,7 +47,7 @@ class ExponentialyWeightedFTS(fts.FTS):
         
 		return mi.dot( flrg.weights() )
         
-	def learn(self, data, sets):
+	def train(self, data, sets):
 		last = {"fuzzyset":"", "membership":0.0}
 		actual = {"fuzzyset":"", "membership":0.0}
 		
diff --git a/sfts.py b/sfts.py
index 3891d45..8b4a1a5 100644
--- a/sfts.py
+++ b/sfts.py
@@ -21,9 +21,9 @@ class SeasonalFLRG(fts.FTS):
 
 class SeasonalFTS(fts.FTS):
 	def __init__(self,name):
-		super(WeightedFTS, self).__init__(1,name)
+		super(SeasonalFTS, self).__init__(1,name)
         
-	def defuzzy(self,data):
+	def forecast(self,data):
         
 		actual = self.fuzzy(data)
         
@@ -36,7 +36,7 @@ class SeasonalFTS(fts.FTS):
         
 		return mi.dot( flrg.weights() )
         
-	def learn(self, data, sets):
+	def train(self, data, sets):
 		last = {"fuzzyset":"", "membership":0.0}
 		actual = {"fuzzyset":"", "membership":0.0}
 		
@@ -50,7 +50,7 @@ class SeasonalFTS(fts.FTS):
 			
 			if count > self.order:
 				if last["fuzzyset"] not in self.flrgs:
-					self.flrgs[last["fuzzyset"]] = WeightedFLRG(last["fuzzyset"])
+					self.flrgs[last["fuzzyset"]] = SeasonalFLRG(last["fuzzyset"])
 			
 				self.flrgs[last["fuzzyset"]].append(actual["fuzzyset"])    
 			count = count + 1
diff --git a/yu.py b/yu.py
index 47ee4b3..55f89e0 100644
--- a/yu.py
+++ b/yu.py
@@ -32,7 +32,7 @@ class WeightedFTS(fts.FTS):
 	def __init__(self,name):
 		super(WeightedFTS, self).__init__(1,name)
         
-	def defuzzy(self,data):
+	def forecast(self,data):
         
 		actual = self.fuzzy(data)
         
@@ -45,7 +45,7 @@ class WeightedFTS(fts.FTS):
         
 		return mi.dot( flrg.weights() )
         
-	def learn(self, data, sets):
+	def train(self, data, sets):
 		last = {"fuzzyset":"", "membership":0.0}
 		actual = {"fuzzyset":"", "membership":0.0}