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| author | Tor Myklebust <tmyklebu@gmail.com> | 2013-12-20 01:50:42 -0500 |
|---|---|---|
| committer | Tor Myklebust <tmyklebu@gmail.com> | 2013-12-20 01:50:42 -0500 |
| commit | d89cc1e28a88a5f943fed096c4bd647f79753c9f (patch) | |
| tree | 861d732e26b21e80826e27572ab2fd461883dff8 /python | |
| parent | 319520b9bb0071527a0be1e0e545ca084ac090ee (diff) | |
| download | spark-d89cc1e28a88a5f943fed096c4bd647f79753c9f.tar.gz spark-d89cc1e28a88a5f943fed096c4bd647f79753c9f.tar.bz2 spark-d89cc1e28a88a5f943fed096c4bd647f79753c9f.zip | |
Whitespace.
Diffstat (limited to 'python')
| -rw-r--r-- | python/pyspark/mllib.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/python/pyspark/mllib.py b/python/pyspark/mllib.py index e7e22166b0..1877404cc1 100644 --- a/python/pyspark/mllib.py +++ b/python/pyspark/mllib.py @@ -276,7 +276,7 @@ class SVMModel(LinearModel): class KMeansModel(object): """A clustering model derived from the k-means method. - >>> data = array([0.0, 0.0, 1.0,1.0, 9.0,8.0, 8.0,9.0]).reshape(4,2) + >>> data = array([0.0,0.0, 1.0,1.0, 9.0,8.0, 8.0,9.0]).reshape(4,2) >>> clusters = KMeansModel.train(sc, sc.parallelize(data), 2, maxIterations=10, runs=30, initialization_mode="random") >>> clusters.predict(array([0.0, 0.0])) == clusters.predict(array([1.0, 1.0])) True |