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From Sean Owen <so...@cloudera.com>
Subject Re: Status of MLLib exporting models to PMML
Date Wed, 12 Nov 2014 02:29:13 GMT
Yes although I think this difference is on purpose as part of that
commercial strategy. If future versions change license it would still be
possible to not upgrade. Or fork / recreate the bean classes. Not worried
so much but it is a good point.
On Nov 11, 2014 10:06 PM, "DB Tsai" <dbtsai@dbtsai.com> wrote:

> I also worry about that the author of JPMML changed the license of
> jpmml-evaluator due to his interest of his commercial business, and he
> might change the license of jpmml-model in the future.
>
> Sincerely,
>
> DB Tsai
> -------------------------------------------------------
> My Blog: https://www.dbtsai.com
> LinkedIn: https://www.linkedin.com/in/dbtsai
>
>
> On Tue, Nov 11, 2014 at 11:43 AM, Sean Owen <sowen@cloudera.com> wrote:
> > Yes, jpmml-evaluator is AGPL, but things like jpmml-model are not;
> they're
> > 3-clause BSD:
> >
> > https://github.com/jpmml/jpmml-model
> >
> > So some of the scoring components are off-limits for an AL2 project but
> the
> > core model components are OK.
> >
> > On Tue, Nov 11, 2014 at 7:40 PM, DB Tsai <dbtsai@dbtsai.com> wrote:
> >>
> >> JPMML evaluator just changed their license to AGPL or commercial
> >> license, and I think AGPL is not compatible with apache project. Any
> >> advice?
> >>
> >> https://github.com/jpmml/jpmml-evaluator
> >>
> >> Sincerely,
> >>
> >> DB Tsai
> >> -------------------------------------------------------
> >> My Blog: https://www.dbtsai.com
> >> LinkedIn: https://www.linkedin.com/in/dbtsai
> >>
> >>
> >> On Tue, Nov 11, 2014 at 10:07 AM, Xiangrui Meng <mengxr@gmail.com>
> wrote:
> >> > Vincenzo sent a PR and included k-means as an example. Sean is helping
> >> > review it. PMML standard is quite large. So we may start with simple
> >> > model export, like linear methods, then move forward to tree-based.
> >> > -Xiangrui
> >> >
> >> > On Mon, Nov 10, 2014 at 11:27 AM, Aris <arisofalaska@gmail.com>
> wrote:
> >> >> Hello Spark and MLLib folks,
> >> >>
> >> >> So a common problem in the real world of using machine learning is
> that
> >> >> some
> >> >> data analysis use tools like R, but the more "data engineers" out
> there
> >> >> will
> >> >> use more advanced systems like Spark MLLib or even Python Scikit
> Learn.
> >> >>
> >> >> In the real world, I want to have "a system" where multiple different
> >> >> modeling environments can learn from data / build models, represent
> the
> >> >> models in a common language, and then have a layer which just takes
> the
> >> >> model and run model.predict() all day long -- scores the models in
> >> >> other
> >> >> words.
> >> >>
> >> >> It looks like the project openscoring.io and jpmml-evaluator are
> some
> >> >> amazing systems for this, but they fundamentally use PMML as the
> model
> >> >> representation here.
> >> >>
> >> >> I have read some JIRA tickets that Xiangrui Meng is interested in
> >> >> getting
> >> >> PMML implemented to export MLLib models, is that happening? Further,
> >> >> would
> >> >> something like Manish Amde's boosted ensemble tree methods be
> >> >> representable
> >> >> in PMML?
> >> >>
> >> >> Thank you!!
> >> >> Aris
> >> >
> >> > ---------------------------------------------------------------------
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> >> > For additional commands, e-mail: user-help@spark.apache.org
> >> >
> >
> >
>

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