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

Gaƫl

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
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