Re: Multinomial regression with spark.ml version of LogisticRegression

Thanks Bryan for that pointer : I will follow it. In the meantime the One vs Rest appears to satisfy the requirements. 2016-05-29 15:40 GMT-07:00 Bryan Cutler : > This is currently being worked on, planned for 2.1 I believe > https://issues.apache.org/jira/browse/SPARK-7159 >

Re: Multinomial regression with spark.ml version of LogisticRegression

This is currently being worked on, planned for 2.1 I believe https://issues.apache.org/jira/browse/SPARK-7159 On May 28, 2016 9:31 PM, "Stephen Boesch" wrote: > Thanks Phuong But the point of my post is how to achieve without using > the deprecated the mllib pacakge. The

Re: Multinomial regression with spark.ml version of LogisticRegression

Thanks Phuong But the point of my post is how to achieve without using the deprecated the mllib pacakge. The mllib package already has multinomial regression built in 2016-05-28 21:19 GMT-07:00 Phuong LE-HONG : > Dear Stephen, > > Yes, you're right, LogisticGradient is in

Re: Multinomial regression with spark.ml version of LogisticRegression

Dear Stephen, Yes, you're right, LogisticGradient is in the mllib package, not ml package. I just want to say that we can build a multinomial logistic regression model from the current version of Spark. Regards, Phuong On Sun, May 29, 2016 at 12:04 AM, Stephen Boesch

Re: Multinomial regression with spark.ml version of LogisticRegression

Hi Phuong, The LogisticGradient exists in the mllib but not ml package. The LogisticRegression chooses either the breeze LBFGS - if L2 only (not elastic net) and no regularization or the Orthant Wise Quasi Newton (OWLQN) otherwise: it does not appear to choose GD in either scenario. If I have

Re: Multinomial regression with spark.ml version of LogisticRegression

Dear Stephen, The Logistic Regression currently supports only binary regression. However, the LogisticGradient does support computing gradient and loss for a multinomial logistic regression. That is, you can train a multinomial logistic regression model with LogisticGradient and a class to solve

Re: Multinomial regression with spark.ml version of LogisticRegression

Followup: just encountered the "OneVsRest" classifier in ml.classsification: I will look into using it with the binary LogisticRegression as the provided classifier. 2016-05-28 9:06 GMT-07:00 Stephen Boesch : > > Presently only the mllib version has the one-vs-all approach

Multinomial regression with spark.ml version of LogisticRegression

Presently only the mllib version has the one-vs-all approach for multinomial support. The ml version with ElasticNet support only allows binary regression. With feature parity of ml vs mllib having been stated as an objective for 2.0.0 - is there a projected availability of the multinomial