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 > >
