I would like to use the output model of a Mahout decision tree
training process as the input model for a Weka based classifier.

As the training of a complex decision tree that is based on millions
of training records is almost impractical for a single node Weka
classifier, I would like to use Mahout to build the model, using for
example Random Forest Partial Implementation.

While the algorithm above can be problematic while training, it is
rather simple to use it for prediction with Weka on a single machine.

On Mahout wiki site it is stated that the data formats for import
include Weka ARFF format, but not for export.

Is it possible to use some of the existing implementations in Mahout
to train models that will be used in production with a simple Weka
based system?

Nobody has ever done it that I have heard of, but the Random Forest
implementation should be simple enough to export to Weka.

You would have to write the code and to do that, you will have to dope out
the format that Weka wants.

On Mon, May 21, 2012 at 9:09 PM, Guy Ernest <[EMAIL PROTECTED]> wrote:

> I would like to use the output model of a Mahout decision tree
> training process as the input model for a Weka based classifier.
>
> As the training of a complex decision tree that is based on millions
> of training records is almost impractical for a single node Weka
> classifier, I would like to use Mahout to build the model, using for
> example Random Forest Partial Implementation.
>
> While the algorithm above can be problematic while training, it is
> rather simple to use it for prediction with Weka on a single machine.
>
> On Mahout wiki site it is stated that the data formats for import
> include Weka ARFF format, but not for export.
>
> Is it possible to use some of the existing implementations in Mahout
> to train models that will be used in production with a simple Weka
> based system?
>

Hi Guy,
there was a discussion about data interoperability some years ago 2008/09 unfortunately the outcome was that in the current state it does not make a lot of sense for mahout to offer models in a standard format like PMML (http://www.dmg.org/pmml-v4-1.html)

http://www.dmg.org/pmml-v4-1.html

You can read the details here:

https://issues.apache.org/jira/browse/MAHOUT-18

/Manuel
On 22.05.2012, at 00:49, Ted Dunning wrote:

> Nobody has ever done it that I have heard of, but the Random Forest
> implementation should be simple enough to export to Weka.
>
> You would have to write the code and to do that, you will have to dope out
> the format that Weka wants.
>
> On Mon, May 21, 2012 at 9:09 PM, Guy Ernest <[EMAIL PROTECTED]> wrote:
>
>> I would like to use the output model of a Mahout decision tree
>> training process as the input model for a Weka based classifier.
>>
>> As the training of a complex decision tree that is based on millions
>> of training records is almost impractical for a single node Weka
>> classifier, I would like to use Mahout to build the model, using for
>> example Random Forest Partial Implementation.
>>
>> While the algorithm above can be problematic while training, it is
>> rather simple to use it for prediction with Weka on a single machine.
>>
>> On Mahout wiki site it is stated that the data formats for import
>> include Weka ARFF format, but not for export.
>>
>> Is it possible to use some of the existing implementations in Mahout
>> to train models that will be used in production with a simple Weka
>> based system?
>>

--
Manuel Blechschmidt
Dortustr. 57
14467 Potsdam
Mobil: 0173/6322621
Twitter: http://twitter.com/Manuel_B

On 22.05.2012 Manuel Blechschmidt wrote:
> there was a discussion about data interoperability some years ago 2008/09
> unfortunately the outcome was that in the current state it does not make a
> lot of sense for mahout to offer models in a standard format like PMML
> (http://www.dmg.org/pmml-v4-1.html)
>
> http://www.dmg.org/pmml-v4-1.html
>
> You can read the details here:
>
> https://issues.apache.org/jira/browse/MAHOUT-18

Which doesn't mean that contributions along these lines would be un-welcome. So
far though non of the committers and contributors had the need to support such a
standard format.
Isabel