FIX spherical k-means confusion in example
@@ -204,9 +204,8 @@ print()
if opts.n_components:
print("Performing dimensionality reduction using LSA")
t0 = time()
- # Vectorizer results are normalized, which makes KMeans behave as
- # spherical k-means for better results. Since LSA/SVD results are
- # not normalized, we have to redo the normalization.
+ # Since LSA/SVD results are not normalized,
+ # we redo the normalization to improve the k-means result.
svd = TruncatedSVD(opts.n_components)
normalizer = Normalizer(copy=False)
lsa = make_pipeline(svd, normalizer)
