Unfortunately, AFAIK custom transformers are not part of the public API so you will have to continue with what you're doing.
On Tue, Jul 28, 2015 at 1:32 PM, Matt Narrell <matt.narr...@gmail.com> wrote: > Hey, > > Our ML ETL pipeline has several complex steps that I’d like to address > with custom Transformers in an ML Pipeline. Looking at the Tokenizer and > HashingTF transformers I see these handy traits (HasInputCol, HasLabelCol, > HasOutputCol, etc.) but they have strict access modifiers. How can I use > these with custom Transformer/Estimator implementations? > > I’m stuck depositing my implementations in org.apache.spark.ml, which is > tolerable for now, but I’m wondering if I’m missing some pattern? > > Thanks, > mn > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
