use cls in train classmethod

Author: swizzard

nltk/classify/naivebayes.py

@@ -179,7 +179,7 @@ def most_informative_features(self, n=100):
         return features[:n]
 
     @classmethod
-    def train(labeled_featuresets, estimator=ELEProbDist):
+    def train(cls, labeled_featuresets, estimator=ELEProbDist):
         """
         :param labeled_featuresets: A list of classified featuresets,
             i.e., a list of tuples ``(featureset, label)``.
@@ -225,7 +225,7 @@ def train(labeled_featuresets, estimator=ELEProbDist):
             probdist = estimator(freqdist, bins=len(feature_values[fname]))
             feature_probdist[label, fname] = probdist
 
-        return NaiveBayesClassifier(label_probdist, feature_probdist)
+        return cls(label_probdist, feature_probdist)
 
 ##//////////////////////////////////////////////////////
 ##  Demo