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ENH: Add support for cosine distance in k-means #12192

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ENH: Add support for cosine distance in k-means #12192

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d1cd600
ENH: Add support for cosine distance in k-means
flaviomartins Sep 28, 2018
90290b6
fix flake8 errors
flaviomartins Oct 1, 2018
6730bcb
raise ValueError for unsupported metrics
flaviomartins Oct 2, 2018
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17 changes: 14 additions & 3 deletions examples/text/plot_document_clustering.py
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Original file line number Diff line number Diff line change
Expand Up @@ -92,6 +92,12 @@
op.add_option("--n-features", type=int, default=10000,
help="Maximum number of features (dimensions)"
" to extract from text.")
op.add_option("--no-remove",
action="store_false", dest="remove_extra", default=True,
help="Keep 'headers', 'footers', 'quotes'")
op.add_option("--metric",
dest="metric", type="str", default="euclidean",
help="Specify the distance metric to use for KMeans.")
op.add_option("--verbose",
action="store_true", dest="verbose", default=False,
help="Print progress reports inside k-means algorithm.")
Expand Down Expand Up @@ -126,8 +132,12 @@ def is_interactive():
print("Loading 20 newsgroups dataset for categories:")
print(categories)

remove = ()
if opts.remove_extra:
remove = ('headers', 'footers', 'quotes')

dataset = fetch_20newsgroups(subset='all', categories=categories,
shuffle=True, random_state=42)
remove=remove, shuffle=True, random_state=42)

print("%d documents" % len(dataset.data))
print("%d categories" % len(dataset.target_names))
Expand Down Expand Up @@ -186,10 +196,11 @@ def is_interactive():

if opts.minibatch:
km = MiniBatchKMeans(n_clusters=true_k, init='k-means++', n_init=1,
init_size=1000, batch_size=1000, verbose=opts.verbose)
init_size=1000, batch_size=1000, verbose=opts.verbose,
metric=opts.metric)
else:
km = KMeans(n_clusters=true_k, init='k-means++', max_iter=100, n_init=1,
verbose=opts.verbose)
verbose=opts.verbose, metric=opts.metric)

print("Clustering sparse data with %s" % km)
t0 = time()
Expand Down
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