Hi, If it's Python I can't help. I'm with Scala.
Jacek On 14 Aug 2016 9:27 p.m., "Evan Zamir" <zamir.e...@gmail.com> wrote: > Thanks, but I should have been more clear that I'm trying to do this in > PySpark, not Scala. Using an example I found on SO, I was able to implement > a Pipeline step in Python, but it seems it is more difficult (perhaps > currently impossible) to make it persist to disk (I tried implementing > _to_java method to no avail). Any ideas about that? > > On Sun, Aug 14, 2016 at 6:02 PM Jacek Laskowski <ja...@japila.pl> wrote: > >> Hi, >> >> It should just work if you followed the Transformer interface [1]. >> When you have the transformers, creating a Pipeline is a matter of >> setting them as additional stages (using Pipeline.setStages [2]). >> >> [1] https://github.com/apache/spark/blob/master/mllib/src/ >> main/scala/org/apache/spark/ml/Transformer.scala >> [2] https://github.com/apache/spark/blob/master/mllib/src/ >> main/scala/org/apache/spark/ml/Pipeline.scala#L107 >> >> Pozdrawiam, >> Jacek Laskowski >> ---- >> https://medium.com/@jaceklaskowski/ >> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark >> Follow me at https://twitter.com/jaceklaskowski >> >> >> On Fri, Aug 12, 2016 at 9:19 AM, evanzamir <zamir.e...@gmail.com> wrote: >> > I'm building an LDA Pipeline, currently with 4 steps, Tokenizer, >> > StopWordsRemover, CountVectorizer, and LDA. I would like to add more >> steps, >> > for example, stemming and lemmatization, and also 1-gram and 2-grams >> (which >> > I believe is not supported by the default NGram class). Is there a way >> to >> > add these steps? In sklearn, you can create classes with fit() and >> > transform() methods, and that should be enough. Is that true in Spark >> ML as >> > well (or something similar)? >> > >> > >> > >> > -- >> > View this message in context: http://apache-spark-user-list. >> 1001560.n3.nabble.com/How-to-add-custom-steps-to-Pipeline- >> models-tp27522.html >> > Sent from the Apache Spark User List mailing list archive at Nabble.com. >> > >> > --------------------------------------------------------------------- >> > To unsubscribe e-mail: user-unsubscr...@spark.apache.org >> > >> >
