Minor mistake in the code,
X, y = make_regression(n_samples=100, n_features=2000)
X[X < 2.5] = 0.0
X = sparse.csr_matrix(X)
sparse_std(X.shape[0], X.shape[1], X.data, X.indices, X.indptr)
On Tue, Mar 25, 2014 at 12:32 AM, Manoj Kumar <
[email protected]> wrote:
> Hi,
>
> Running the following code as a script gives me the following error,
> Segmentation fault (core dumped). However if I run it in the interpreter
> everything works (making me wonder how to debug it)
>
> from scipy import sparse
> from sklearn.datasets import make_regression
> from sklearn.linear_model.base import sparse_center_data
> from sklearn.linear_model.cd_fast import sparse_std
>
> X, y = make_regression(n_samples=100, n_features=2000)
> X[X < 2.5] = 0.0
> Xs = sparse.csr_matrix(X)
> sparse_std(X.shape[0], X.shape[1], X.data, X.indices, X.indptr)
>
> Is anyone else able to reproduce the same behaviour? Or am I missing
> something as usual? Any help would be greatly appreciated.
>
> --
> Regards,
> Manoj Kumar,
> Mech Undergrad
> http://manojbits.wordpress.com
>
--
Regards,
Manoj Kumar,
Mech Undergrad
http://manojbits.wordpress.com
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