Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/11844#discussion_r62716684
--- Diff: docs/ml-clustering.md ---
@@ -104,4 +104,48 @@ Refer to the [Java API
docs](api/java/org/apache/spark/ml/clustering/LDA.html) f
{% include_example java/org/apache/spark/examples/ml/JavaLDAExample.java %}
</div>
-</div>
\ No newline at end of file
+</div>
+
+## Bisecting k-means
+
+
+Bisecting k-means is a kind of [hierarchical
clustering](https://en.wikipedia.org/wiki/Hierarchical_clustering) using a
+divisive (or "top-down") approach: all observations start in one cluster,
and splits are performed recursively as one
+moves down the hierarchy.
+
+Bisecting K-means can often be much faster than regular K-means, but it
will generally produce a different clustering.
+
+`BisectingKMeans` is implemented as an `Estimator` and generates a
`BisectingKMeansModel` as the base model.
+
+The implementation in ML has the following parameters:
+
+* *k*: the desired number of leaf clusters (default: 4). The actual number
could be smaller if there are no divisible leaf clusters.
--- End diff --
Your point is valid - this would be a bit out of place in the ml docs. I
also agree that is does add a burden of keeping params and defaults in sync
with the code. There's a good argument that the param doc lives in the API docs
(as it does now for ml). Still, there's also a decent argument for having more
detailed docs on params in the user guide, though perhaps only for very
important ones (like an initialization scheme, or algorithm type etc).
Indeed, scikit-learn user guide and API docs seem to follow this style (as
an example).
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