fine with me but do you push the logic further to any linear estimator ?
For example in Ridge we also have normalize=False by default.

I would say that LassoLars is more the exception than the norm.

Alex

On Wed, Oct 31, 2012 at 11:53 AM, Jaques Grobler
<jaquesgrob...@gmail.com> wrote:
> It makes sense to me to make the change - however the scikit-learn users
> would just
> need to be warned about this. Perhaps for now we can just add a warning that
> the API
> will be changing as to make users well aware (before actually changing the
> API)
> and that they must manually set it up in the meanwhile so that the default
> setting change doesn't
> affect them. That might lessen the 'breakage' when the change is
> implemented.
> Anyway, rant aside, I think it makes good sense to set it to True by default
>
> 2012/10/31 Olivier Grisel <olivier.gri...@ensta.org>
>>
>> 2012/10/31 Gael Varoquaux <gael.varoqu...@normalesup.org>:
>> >
>> > I want to change this (warning backward compatibility breakage :$ ). I
>> > want to change Lasso to have normalize=True, because in my experience
>> > this is a sane behavior. This would imply, for consistency, changing
>> > ElasticNet to also have normalize=True. We would have to put the usual
>> > warnings.
>> >
>> > What do people think? In one sens this change can trick people and break
>> > in a subtle way the code that they are currently running. However, the
>> > current situation also breaks in subtle way people's expectation.
>>
>> +1
>>
>> --
>> Olivier
>> http://twitter.com/ogrisel - http://github.com/ogrisel
>>
>>
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