Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/10610#discussion_r51303389
--- Diff: python/pyspark/mllib/clustering.py ---
@@ -170,7 +173,43 @@ class KMeans(object):
@since('0.9.0')
def train(cls, rdd, k, maxIterations=100, runs=1,
initializationMode="k-means||",
seed=None, initializationSteps=5, epsilon=1e-4,
initialModel=None):
- """Train a k-means clustering model."""
+ """
+ Train a k-means clustering model.
+
+ :param rdd:
+ Train with a RDD of data points.
+ :param k:
+ Number of clusters to create.
+ :param maxIterations:
+ Maximum number of iterations allowed.
+ (default: 100)
+ :param runs:
+ Number of runs to execute in parallel. The best model according
+ to the cost function will be returned (deprecated in 1.6.0).
+ (default: 1)
+ :param initializationMode:
+ The initialization algorithm. This can be either "random" or
+ "k-means||".
+ (default: "k-means||")
+ :param seed:
+ Random seed value for cluster initialization. Set as None to
+ generate seed based on system time.
+ (default: None)
+ :param initializationSteps:
+ Set the number of steps for the k-means|| initialization mode.
+ This is an advanced setting -- the default of 5 is almost
+ always enough.
+ (default: 5)
+ :param epsilon:
+ Set the distance threshold within which we've consider centers
--- End diff --
Oh, I agree that `Set` should not be here, I meant to leave that off... We
should only start with `Set` if the method is specifically to set that
parameter.
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