[GitHub] spark pull request: [SPARK-3012] Standardized Distance Functions b...

[mengxr <gi...@git.apache.org>]

Github user mengxr commented on the pull request:

    https://github.com/apache/spark/pull/1964#issuecomment-54254431
  
    @yu-iskw @erikerlandson @dlwh I prefer simple types for parameters for model serialization and consistent APIs across languages. In a predictive model, we should store the training parameters that used to train this model, and it would be nice to use simple-typed parameters. Another concern is Python API. If we pass in a distance implementation, we also need to define its Python counterpart for API consistency, which is not needed by PySpark's k-means because it calls Scala's implementation through serialization.
    
    For Spark's k-means, it should be good enough to support common and predefined distance measures, via Breeze.


---
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 infrastructure@apache.org or file a JIRA ticket
with INFRA.
---

---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org