Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/11119#discussion_r77017435
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
---
@@ -258,6 +290,27 @@ class KMeans @Since("1.5.0") (
@Since("1.5.0")
def setSeed(value: Long): this.type = set(seed, value)
+ /** @group setParam */
+ @Since("2.0.0")
+ def setInitialModel(value: KMeansModel): this.type = set(initialModel,
value)
--- End diff --
The way this PR is currently, you have to set initial model AND set k. I
think that's annoying. This should work:
````scala
val kmeansModel = new KMeans().setInitialModel(model).fit(df)
````
If a user sets the initial model and explicitly sets k to some conflicting
value, I think we should throw an error. However, if they don't set anything
for k, we should just use the initial model k. Currently, k defaults to 2 so an
error gets thrown (unless the initial model has 2 centers).
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