Unfortunately, the Pipelines API doesn't have multiclass logistic regression yet, only binary. It's really a matter of modifying the current implementation; I just added a JIRA for it: https://issues.apache.org/jira/browse/SPARK-7159
You'll need to use the old LogisticRegression API to do multiclass for now, until that JIRA gets completed. (If you're interested in doing it, let me know via the JIRA!) Joseph On Fri, Apr 24, 2015 at 3:26 AM, Selim Namsi <selim.na...@gmail.com> wrote: > Hi, > > I just started using spark ML pipeline to implement a multiclass classifier > using LogisticRegressionWithLBFGS (which accepts as a parameters number of > classes), I followed the Pipeline example in ML- guide and I used > LogisticRegression class which calls LogisticRegressionWithLBFGS class : > > val lr = new LogisticRegression().setMaxIter(10).setRegParam(0.01) > > the problem is that LogisticRegression doesn't take numClasses as > parameters > > Any idea how to solve this problem? > > Thanks > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Multiclass-classification-using-Ml-logisticRegression-tp22644.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 > >
