Yes, a model saved with the save method can be read back only by the load 
method in the RandomForestModel object.

Unfortunately, I don’t know any better mechanism for what you are trying to do. 
There was a discussion on this topic a few days ago, so if you search the 
mailing list archives, you may be able to find other alternatives.

Mohammed
Author: Big Data Analytics with 
Spark<http://www.amazon.com/Big-Data-Analytics-Spark-Practitioners/dp/1484209656/>

From: Jay Luan [mailto:jaylu...@gmail.com]
Sent: Wednesday, February 10, 2016 7:27 PM
To: Mohammed Guller
Cc: user@spark.apache.org
Subject: RE: [MLLIB] Best way to extract RandomForest decision splits


Thanks for the reply, I'd like to export the decision splits for each tree out 
to an external file which is read elsewhere not using spark. As far as I know, 
saving a model to a path will save a bunch of binary files which can be loaded 
back into spark. Is this correct?
On Feb 10, 2016 7:21 PM, "Mohammed Guller" 
<moham...@glassbeam.com<mailto:moham...@glassbeam.com>> wrote:

Why not use the save method from the RandomForestModel class to save a model at 
a specified path?



Mohammed

Author: Big Data Analytics with Spark





-----Original Message-----
From: jluan [mailto:jaylu...@gmail.com<mailto:jaylu...@gmail.com>]
Sent: Wednesday, February 10, 2016 5:57 PM
To: user@spark.apache.org<mailto:user@spark.apache.org>
Subject: [MLLIB] Best way to extract RandomForest decision splits



I've trained a RandomForest classifier where I can print my model's decisions

using model.toDebugString



However I was wondering if there's a way to extract tree programmatically by

traversing the nodes or in some other way such that I can write my own

decision file rather than just a debug string.







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