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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.
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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,
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
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 x...@palantir.com wrote:
Hi,
I am an intern at PalantirTech and we are building some stuff on top
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 sandy.r...@cloudera.com
