Sorry, I meant "a way to only calculate the alphas". The problem is that I
need to do this for a large number of datasets, so less calculations equals
more speed!
2012/7/30 Néstor Espinoza <[email protected]>
> Dear all,
>
> First of all, thanks a lot for your work with the Scikit-learn package,
> it is great and saved a lot of implementation time for me.
>
> I've been having some time figuring out how to use the LASSO (via LARS),
> though. I was trained with the "gamma" notation for the minimization
> function for the LASSO (i.e. the notation used in Tibshirani's
> paper<http://www-stat.stanford.edu/~tibs/lasso/lasso.pdf>),
> so I'm really lost in figuring out what the relation between the alpha
> parameter (according to the sci-kit-learn notation of the minimizing
> function <http://scikit-learn.org/0.10/modules/linear_model.html#lasso>)
> and the gamma parameter. I know how to get the grid of "gammas" that span
> the possible ranges of values, but I can't seem to find the relation
> between that and the grid of possible alpha parameters.
>
> However, after reading through the tutorials, I found out that there's
> actually a function which returns a "grid" of possible alphas, the
> lasso_path<http://scikit-learn.org/0.10/modules/generated/sklearn.linear_model.lasso_path.html#sklearn.linear_model.lasso_path>function
> in linear_models(). However, this also computes a list of "models"
> along this grid...is there a way to only return the alphas? I need this
> because I have my own version of Cross-Validation coded, which I really
> need to use. For that matter, I only need a grid of alphas where to test
> the model.
>
> Cheers and thanks in advance for your responses!
>
> --
> Néstor
>
--
Néstor
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