Hopefully the new pipeline API addresses this problem. We have a code example here:
https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/ml/SimpleTextClassificationPipeline.scala -Xiangrui On Mon, Dec 29, 2014 at 5:22 AM, andy petrella <andy.petre...@gmail.com> wrote: > Here is what I did for this case : https://github.com/andypetrella/tf-idf > > > Le lun 29 déc. 2014 11:31, Sean Owen <so...@cloudera.com> a écrit : > >> Given (label, terms) you can just transform the values to a TF vector, >> then TF-IDF vector, with HashingTF and IDF / IDFModel. Then you can >> make a LabeledPoint from (label, vector) pairs. Is that what you're >> looking for? >> >> On Mon, Dec 29, 2014 at 3:37 AM, Yao <y...@ford.com> wrote: >> > I found the TF-IDF feature extraction and all the MLlib code that work >> > with >> > pure Vector RDD very difficult to work with due to the lack of ability >> > to >> > associate vector back to the original data. Why can't Spark MLlib >> > support >> > LabeledPoint? >> > >> > >> > >> > -- >> > View this message in context: >> > http://apache-spark-user-list.1001560.n3.nabble.com/Using-TF-IDF-from-MLlib-tp19429p20876.html >> > Sent from the Apache Spark User List mailing list archive at Nabble.com. >> > >> > --------------------------------------------------------------------- >> > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> > For additional commands, e-mail: user-h...@spark.apache.org >> > >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org >> > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
