Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/12967#discussion_r62425641
--- Diff: python/pyspark/ml/tuning.py ---
@@ -143,6 +145,8 @@ def getEvaluator(self):
class CrossValidator(Estimator, ValidatorParams):
"""
+ .. note:: Experimental
--- End diff --
Right now the Scala doc in ml is :-1:
>
> * K-means clustering with support for k-means|| initialization proposed
by Bahmani et al.
> *
> * @see [[http://dx.doi.org/10.14778/2180912.2180915 Bahmani et al.,
Scalable k-means++.]]
>
The mllib one is:
> * K-means clustering with a k-means++ like initialization mode
> * (the k-means|| algorithm by Bahmani et al).
> *
> * This is an iterative algorithm that will make multiple passes over the
data, so any RDDs given
> * to it should be cached by the user.
>
I'm happy to try write a longer scaladoc on KMeans or we could just copy
the link over to match Scala - whats your preference?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
