Github user zhengruifeng commented on a diff in the pull request:
https://github.com/apache/spark/pull/11974#discussion_r57827407
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala ---
@@ -503,6 +525,39 @@ object KMeans {
* function will be returned. (default: 1)
* @param initializationMode The initialization algorithm. This can
either be "random" or
* "k-means||". (default: "k-means||")
+ * @param miniBatchFraction fraction of the input data set that should
be used for
+ * one iteration of EM. Default value 1.0.
+ * @param seed Random seed for cluster initialization. Default is to
generate seed based
+ * on system time.
+ */
+ @Since("2.0.0")
+ def train(
--- End diff --
What about createing another object named MiniBatchKMenas and put the API
into it? It is convenient to use it as a static method.
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