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
