Just my 0.02$ as a user: I was also a confused/put-off by `alpha` and 
`l1_ratio` when I first explored SGDClassifier, I found those names to 
be pretty inconsistent --- plus I tend to call my regularization 
parameters `lambda` and use `alpha` for learning rates. I'm sure other 
people associate yet other meanings with alpha/use other names for the 
regularization parameter.  `l1_reg`/`l2_reg` would be much 
better/conciser names, it would be nice if those could be used all 
throughout sklearn.

Cheers

Thomas


On 2013-11-08 09:20, Vlad Niculae wrote:
> Re: the discussion we had at PyCon.fr, I noticed that the internal
> elastic net coordinate descent functions are parametrized with
> `l1_reg` and `l2_reg`, but the exposed classes and functions have
> `alpha` and `l1_ratio`.  Only yesterday there was somebody on IRC who
> couldn't match Ridge with ElasticNet because of this parametrization.
>
> On Fri, Nov 8, 2013 at 9:02 AM, Olivier Grisel <olivier.gri...@ensta.org> 
> wrote:
>> About the LBFGS-B residuals (non-)issue I was probably confused by the
>> overlapping on the plot and mis-interpreted the location of the PG-l1
>> and PG-l2 curves.
>>
>> --
>> Olivier
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