zhengruifeng commented on a change in pull request #27758: [SPARK-31007][ML]
KMeans optimization based on triangle-inequality
URL: https://github.com/apache/spark/pull/27758#discussion_r386785281
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/clustering/DistanceMeasure.scala
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@@ -24,16 +24,60 @@ import org.apache.spark.mllib.util.MLUtils
private[spark] abstract class DistanceMeasure extends Serializable {
+ /**
+ * Radii of centers used in triangle inequality to obtain useful bounds to
find
+ * closest centers.
+ *
+ * @see <a
href="https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf";>Charles Elkan,
+ * Using the Triangle Inequality to Accelerate k-Means</a>
+ *
+ * @return Radii of centers. If distance between point x and center c is
less than
+ * the radius of center c, then center c is the closest center to
point x.
+ */
+ def computeRadii(centers: Array[VectorWithNorm]): Array[Double] = {
Review comment:
You are right, I should remove this. Not all distance can be expected to
have such triangle-inequality.
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