Hello, In MLLib with Spark 1.4, I was able to eval a model by loading it and using `predict` on a vector of features. I would train on Spark but use my model on my workflow.
In `spark.ml` it seems like the only way to eval is to use `transform` which only takes a DataFrame.To build a DataFrame i need a sparkContext or SQLContext, so it doesn't seem to be possible to eval outside of Spark. Is there either a way to build a DataFrame without a sparkContext, or predict with a vector or list of features without a DataFrame? Thanks
