Hello,I'm trying to save a pipeline with a random forest classifier. If I try
to save the pipeline, it complains that the classifier is not Writable, and
indeed the classifier itself doesn't have a write function. There's a pull
request that's been merged that enables this for Spark 2.0 (any dates around
when that'll release?). I am, however, using the Spark Cassandra Connector
which doesn't seem to be able to create a CqlContext with spark 2.0 snapshot
builds. Seeing that ML Lib's random forest classifier supports storing and
loading models, is there a way to create a Spark ML pipeline in Spark 1.6 with
a random forest classifier that'll allow me to store and load the model? The
model takes significant amount of time to train, and I really don't want to
have to train it every time my application launches.
Thanks,Ashic.
