There have been some comments about using Pipelines outside of ML, but I have not yet seen a real need for it. If a user does want to use Pipelines for non-ML tasks, they still can use Transformers + PipelineModels. Will that work?
On Fri, Mar 25, 2016 at 8:05 AM, Jacek Laskowski <ja...@japila.pl> wrote: > Hi, > > After few weeks with spark.ml now, I came to conclusion that > Transformer concept from Pipeline API (spark.ml/MLlib) should be part > of DataFrame (SQL) where they fit better. Are there any plans to > migrate Transformer API (ML) to DataFrame (SQL)? > > Pozdrawiam, > Jacek Laskowski > ---- > https://medium.com/@jaceklaskowski/ > Mastering Apache Spark http://bit.ly/mastering-apache-spark > Follow me at https://twitter.com/jaceklaskowski > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org > For additional commands, e-mail: dev-h...@spark.apache.org > >
