2012/1/9 Peter Prettenhofer <[email protected]>:
> 2012/1/8 Mathieu Blondel <[email protected]>:
>> If I'm not mistaken (I just read the source code on github), the copy
>> that Peter is experiencing is due to ravel() in this method:
>> https://github.com/scipy/scipy/blob/master/scipy/sparse/compressed.py#L264
>>
>> This method in turn invokes csr_matvecs which is implemented here:
>> https://github.com/scipy/scipy/blob/master/scipy/sparse/sparsetools/csr.h#L1010
>>
>> This method takes a sparse matrix and a flat array (C-style ordered)
>> as inputs. The advantage of using ravel() here is that another
>> implementation is not needed to handle Fortran-style arrays. However,
>> it does result in a copy.
>>
>> In predict, SGDClassifier does a safe_sparse_dot(X, self.coef_.T).
>> Therefore, if coef_ is Fortran-style, coef_.T becomes C-style, which
>> is the format expected by ravel() to avoid a copy.
>
> I just checked: The issue does only apply to multi class classification!
> For binary classification ``coef_`` is a one dimensional array which
> is both c and fortran style.
>
> ``ravel`` is only used in the binary case so it is not responsible for
> the copy.
>

BTW: I just looked at csr_matrix.__mul__ and
sparse.compressed._mul_multivector - there are ravels all over the
place that trigger a copy of the view.


-- 
Peter Prettenhofer

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