Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/13291#discussion_r64699018
--- Diff: python/pyspark/ml/clustering.py ---
@@ -227,15 +242,15 @@ class KMeans(JavaEstimator, HasFeaturesCol,
HasPredictionCol, HasMaxIter, HasTol
.. versionadded:: 1.5.0
"""
- k = Param(Params._dummy(), "k", "number of clusters to create",
+ k = Param(Params._dummy(), "k", "The number of clusters to create.
Must be > 1.",
typeConverter=TypeConverters.toInt)
initMode = Param(Params._dummy(), "initMode",
- "the initialization algorithm. This can be either
\"random\" to " +
+ "The initialization algorithm. This can be either
\"random\" to " +
"choose random points as initial cluster centers, or
\"k-means||\" " +
"to use a parallel variant of k-means++",
typeConverter=TypeConverters.toString)
- initSteps = Param(Params._dummy(), "initSteps", "steps for k-means
initialization mode",
- typeConverter=TypeConverters.toInt)
+ initSteps = Param(Params._dummy(), "initSteps", "The number of steps
for k-means|| " +
--- End diff --
Since were copying this over might as well also include "his is an advanced
setting -- the default of 5 is almost always enough." from the scala side?
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