At least for me, that change helps the example be less mysterious...and helps
clarify what alpha means in context. (though I probably should have known
weights == coefficients on linear models).
> Date: Tue, 30 Apr 2013 08:06:18 +0200
> From: [email protected]
> To: [email protected]
> Subject: Re: [Scikit-learn-general] Possible Incorrect Labels on "Lasso and
> ElasticNet" example page?
>
> Hi,
>
> It was a cosmetic variant: 'weights' and 'coefficients' mean the same for
> linear models. And as iterations are done in a logarithmic way, the x
> axis was correct to a scaling.
>
> None the less, I fixed the example to be less confusing:
> https://github.com/scikit-learn/scikit-learn/commit/f924d3e466305ba1eb26e2fadb84eb54225a0437
>
> Thanks
>
> Gaël
>
> On Tue, Apr 30, 2013 at 05:44:19AM +0100, _ Rolpher wrote:
> > I'm looking at the example page for Lasso and ElasticNet ( http://
> > scikit-learn.org/0.11/auto_examples/linear_model/
> > plot_lasso_coordinate_descent_path.html ). The code is clearly plotting
> > coefficients, but the ylabel says "weights". Similarly, the xlabel is "-log
> > (Lambda)", but it looks like it's actually the number of iterations.
>
> > Do I have that right? If so, I could make a pull request with the corrected
> > example later.
>
> > On a separate note, why does lasso_path in the example return instances of
> > an
> > `ElasticNet` model, as opposed to a `Lasso` model? Are they equivalent
> > when l1
> > =1.0 (or rho=1.0 ... slightly confused on the parameter naming as compared
> > to R
> > or Octave packages).
>
> > Thanks,
>
> > Rolpher
>
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>
> --
> Gael Varoquaux
> Researcher, INRIA Parietal
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