Fix comment typos in 04-KNN.py (examples/05-vector)
Thanks to Fixes
@@ -40,10 +40,10 @@ for page in range(1, 10):
m.append(Document(s, type=p, stemmer=None))
# Train k-Nearest Neighbor on the model.
-# Note that this is a only simple example: to build a robust classifier
+# Note that this is only a simple example: to build a robust classifier
# you would need a lot more training data (e.g., tens of thousands of tweets).
# The more training data, the more statistically reliable the classifier becomes.
-# The only way to really know if you're classifier is working correctly
+# The only way to really know if your classifier is working correctly
# is to test it with testing data, see the documentation for Classifier.test().
classifier = KNN(baseline=None) # By default, baseline=MAJORITY
for document in m: # (classify unknown documents with the most frequent type).
