Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/117#discussion_r10775121
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala ---
@@ -114,27 +126,60 @@ class KMeans private (
* performance, because this is an iterative algorithm.
*/
def run(data: RDD[Array[Double]]): KMeansModel = {
- // TODO: check whether data is persistent; this needs RDD.storageLevel
to be publicly readable
+ run(data.map(v => Vectors.dense(v)))
+ }
+
+ /**
+ * Train a K-means model on the given set of points; `data` should be
cached for high
+ * performance, because this is an iterative algorithm.
+ */
+ def run(data: RDD[Vector])(implicit d: DummyImplicit): KMeansModel = {
--- End diff --
If the implicit is done to deal with type erasure on RDDs of different
forms, that's not a great solution. We might instead rename the old method that
ran on arrays, or give this one a different name.
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