2012/12/14 Shishir Pandey <[email protected]>:
> Hi
>
> I am trying to trying to find the regression matrix \beta. In the following:
>
> Y = X \beta + \epsilon
>
> Y - m x n matrix. (sparse matrix)
> X - m x k matrix. (sparse matrix)
> \beta - k x n matrix
>
> I try to fit the SGDRegressor as fit(X,Y). It gives a value error:
> ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
>
> I see in the documentation Y can only be a vector of type [n_samples]. Is
> there a way in which I can use SGDRegressor with Y being a matrix.

Right now, the SGDRegressor linear model accepts a single output. You
will have to slice the Y matrix into column with shape `(n_samples,)`
and run `n_outputs` independent linear regression and then aggregate
the `coef_` vectors to find you beta matrix.

--
Olivier
http://twitter.com/ogrisel - http://github.com/ogrisel

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