Hi Eustache,
that's quite a bug - thanks for reporting - I fixed it and added a sparsify
test to test_common.py - pushed directly to master.
thanks,
Peter
2013/11/4 Eustache DIEMERT <eusta...@diemert.fr>
> Hi List,
>
> I'm currently working on some performance documentation [1] and I wanted
> to micro-benchmark the dense vs sparse coefficients case.
>
> I created a self-contained script and wanted to bench it using
> line_profiler, but it seems that after the call to `sparsify()` my
> SGDRegressor can't predict anymore (crashes with a dimensions mismatch
> error).
>
> Here is a gist to reproduce that: [2].
>
> The weird thing is that the coeffs_ attribute changes shape after the call
> to sparsify:
> (30,) -> (1, 30)
> where 30 equals to n_features in my case.
>
> Any idea or explanation welcome !
>
> [1] https://github.com/scikit-learn/scikit-learn/pull/2488
> [2] https://gist.github.com/oddskool/7300982
>
> PS: The stack trace:
> """
> Traceback (most recent call last):
> File "/usr/local/bin/kernprof.py", line 233, in <module>
> sys.exit(main(sys.argv))
> File "/usr/local/bin/kernprof.py", line 221, in main
> execfile(script_file, ns, ns)
> File "sparsity_benchmark.py", line 52, in <module>
> score(y_test, clf.predict(X_test), 'sparse model')
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/stochastic_gradient.py",
> line 903, in predict
> return self.decision_function(X)
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/stochastic_gradient.py",
> line 888, in decision_function
> scores = safe_sparse_dot(X, self.coef_) + self.intercept_
> File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/extmath.py",
> line 190, in safe_sparse_dot
> ret = a * b
> File "/usr/lib/python2.7/dist-packages/scipy/sparse/base.py", line 311,
> in __rmul__
> return (self.transpose() * tr).transpose()
> File "/usr/lib/python2.7/dist-packages/scipy/sparse/base.py", line 278,
> in __mul__
> raise ValueError('dimension mismatch')
> ValueError: dimension mismatch
> """
>
>
>
>
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