In this case, the w that will be returned by in .coef will be of shape
(n_samples, n_features) if I follow the nomenclature correctly?
I guess the 'rule' is that n_features should always represent the number of
columns? I only came across this because I was working with some square
matrix, and I kept getting stupid results until I actually did some
checking on what the orientation of w was.
On Fri, Nov 9, 2012 at 4:57 PM, Gael Varoquaux <
[email protected]> wrote:
> On Fri, Nov 09, 2012 at 04:32:35PM +0100, federico vaggi wrote:
> > Is there any reason why in the case of a matrix y, the coefficients
> returned by
> > the linear regression seem to be a transpose of the actual coefficient
> matrix?
> > I am sure this is just a case of syntax/convenience, but I was actually
> trying
> > to understand the logic.
>
> The logic is that in the scikit-learn, every 2D array should be of shape
> (n_items, n_features).
>
> G
>
>
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