You are viewing a plain text version of this content. The canonical link for it is here.

Posted to user@spark.apache.org by Yanbo Liang <yb...@gmail.com> on 2015/08/05 04:12:44 UTC

Re: Difference between RandomForestModel and RandomForestClassificationModel

The old mllib API will use RandomForest.trainClassifier() to train a
RandomForestModel;
the new mllib API (AKA ML) will use RandomForestClassifier.train() to train
a RandomForestClassificationModel.
They will produce the same result for a given dataset.

2015-07-31 1:34 GMT+08:00 Bryan Cutler <cu...@gmail.com>:

> Hi Praveen,
>
> In MLLib, the major difference is that RandomForestClassificationModel
> makes use of a newer API which utilizes ML pipelines.  I can't say for
> certain if they will produce the same exact result for a given dataset, but
> I believe they should.
>
> Bryan
>
> On Wed, Jul 29, 2015 at 12:14 PM, praveen S <my...@gmail.com> wrote:
>
>> Hi
>> Wanted to know what is the difference between
>> RandomForestModel and RandomForestClassificationModel?
>> in Mlib.. Will they yield the same results for a given dataset?
>>
>
>