DOC Added extra documentation in MiniBatchKMean for reassignment_ratio
@@ -1802,6 +1802,12 @@ class MiniBatchKMeans(_BaseKMeans):
-----
See https://www.eecs.tufts.edu/~dsculley/papers/fastkmeans.pdf
+ When there are too few points in the dataset, some centers may be
+ duplicated, which means that a proper clustering in terms of the number
+ of requesting clusters and the number of returned clusters will not
+ always match. One solution is to set `reassignment_ratio=0`, which
+ prevents reassignments of clusters that are too small.
+
Examples
--------
>>> from sklearn.cluster import MiniBatchKMeans
