you, I'd be happy to send a PR to your branch.
>>>> * In addition to the generated test data, We may use some real-world
>> data for testing. In my implementation, I added the test data from
>> https://onlinecourses.science.psu.edu/stat504/node/223. Please check my
&g
/223. Please check my
> test suite.
> >>
> >> -Gang
> >> Sent from my iPad
> >>
> >>> On 2014年6月27日, at 下午6:03, "xwei" <[hidden email]> wrote:
> >>>
> >>>
> >>> Yes, that's what we did: adding
, at 下午6:03, "xwei" <[hidden email]> wrote:
>>>
>>>
>>> Yes, that's what we did: adding two gradient functions to Gradient.scala
>>> and
>>> create PoissonRegression and GammaRegression using these gradients. We made
>>> a PR on this
t; create PoissonRegression and GammaRegression using these gradients. We made
> > a PR on this.
> >
> >
> >
> > --
> > View this message in context:
> > http://apache-spark-developers-list.1001551.n3.nabble.com/Contributing-to-MLlib-on-GLM-tp7033p7088.htm
is.
>
>
>
> --
> View this message in context:
> http://apache-spark-developers-list.1001551.n3.nabble.com/Contributing-to-MLlib-on-GLM-tp7033p7088.html
> Sent from the Apache Spark Developers List mailing list archive at Nabble.com.
Yes, that's what we did: adding two gradient functions to Gradient.scala and
create PoissonRegression and GammaRegression using these gradients. We made
a PR on this.
--
View this message in context:
http://apache-spark-developers-list.1001551.n3.nabble.com/Contributing-to-MLlib-o
Well, as you said, MLLib already supports GLM in a sense. Except they only
support two link functions - identity (linear regression) and logit
(logistic regression). It should not be too hard to add other link
functions, as all you have to do is add a different gradient function for
Poisson/Gamma,
Hi Xiaokai,
Also take a look through Xiangrui's slides from HadoopSummit a few weeks
back: http://www.slideshare.net/xrmeng/m-llib-hadoopsummit The roadmap
starting at slide 51 will probably be interesting to you.
Andrew
On Tue, Jun 17, 2014 at 7:37 PM, Sandy Ryza wrote:
> Hi Xiaokai,
>
> I
Hi Xiaokai,
I think MLLib is definitely interested in supporting additional GLMs. I'm
not aware of anybody working on this at the moment.
-Sandy
On Tue, Jun 17, 2014 at 5:00 PM, Xiaokai Wei wrote:
> Hi,
>
> I am an intern at PalantirTech and we are building some stuff on top of
> MLlib. In P
Hi,
I am an intern at PalantirTech and we are building some stuff on top of
MLlib. In Particular, GLM is of great interest to us. Though
GeneralizedLinearModel in MLlib 1.0.0 has some important GLMs such as
Logistic Regression, Linear Regression, some other important GLMs like
Poisson Regression
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