Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/9952#discussion_r46861703
--- Diff: docs/mllib-clustering.md ---
@@ -718,6 +718,34 @@ sameModel = LDAModel.load(sc, "myModelPath")
</div>
+## Bisecting k-means
+
+Bisecting k-means is a kind of [hierarchical
clustering](https://en.wikipedia.org/wiki/Hierarchical_clustering).
+Hierarchical clustering is one of the most commonly used method of
cluster analysis which seeks to build a hierarchy of clusters.
+Strategies for hierarchical clustering generally fall into two types:
+
+- Agglomerative: This is a "bottom up" approach: each observation starts
in its own cluster, and pairs of clusters are merged as one moves up the
hierarchy.
+- Divisive: This is a "top down" approach: all observations start in one
cluster, and splits are performed recursively as one moves down the hierarchy.
+
+Bisecting k-means algorithm is a kind of divisive algorithms.
+Because it is too difficult to implement a agglomerative algorithm as a
distributed algorithm on Spark.
--- End diff --
Remove this line please; it may not always be the case.
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