Hi All, Request help with problem mentioned in the mail below. I have an existing random forest model in R which needs to be deployed on Spark. I am trying to recreate the model in Spark but facing the problem mentioned below.
Thanks, Neha On Jun 24, 2016 5:10 PM, wrote: > > Hi Sun, > > I am trying to build a model in Spark. Here are the parameters which were used in R for creating the model, I am unable to figure out how to specify a similar input to the random forest regressor in Spark so that I get a similar model in Spark. > > https://cran.r-project.org/web/packages/randomForest/randomForest.pdf > > mytry=3 > > ntree=500 > > importance=TRUE > > maxnodes = NULL > > On May 31, 2016 7:03 AM, "Sun Rui" <[email protected]> wrote: >> >> I mean train random forest model (not using R) and use it for prediction together using Spark ML. >> >>> On May 30, 2016, at 20:15, Neha Mehta <[email protected]> wrote: >>> >>> Thanks Sujeet.. will try it out. >>> >>> Hi Sun, >>> >>> Can you please tell me what did you mean by "Maybe you can try using the existing random forest model" ? did you mean creating the model again using Spark MLLIB? >>> >>> Thanks, >>> Neha >>> >>> >>> >>>> >>>> From: sujeet jog <[email protected]> >>>> Date: Mon, May 30, 2016 at 4:52 PM >>>> Subject: Re: Can we use existing R model in Spark >>>> To: Sun Rui <[email protected]> >>>> Cc: Neha Mehta <[email protected]>, user <[email protected]> >>>> >>>> >>>> Try to invoke a R script from Spark using rdd pipe method , get the work done & and receive the model back in RDD. >>>> >>>> >>>> for ex :- >>>> . rdd.pipe("<FileName.R>") >>>> >>>> >>>> On Mon, May 30, 2016 at 3:57 PM, Sun Rui <[email protected]> wrote: >>>>> >>>>> Unfortunately no. Spark does not support loading external modes (for examples, PMML) for now. >>>>> Maybe you can try using the existing random forest model in Spark. >>>>> >>>>>> On May 30, 2016, at 18:21, Neha Mehta <[email protected]> wrote: >>>>>> >>>>>> Hi, >>>>>> >>>>>> I have an existing random forest model created using R. I want to use that to predict values on Spark. Is it possible to do the same? If yes, then how? >>>>>> >>>>>> Thanks & Regards, >>>>>> Neha >>>>> >>>>> >>>> >>>> >>> >>
