Jacob,

which file are you referring to? I cannot find the line you mentioned
in the plot_sgd_ols file...
It seems like an learning rate issue - I strongly recommend to
standardizing your inputs first.

best,
 Peter

2012/5/22 Jacob VanderPlas <[email protected]>:
> Hi,
> I've been playing with the SGD classifier (using the current master
> branch), and found that when there is a large range in x, the classifier
> fails.  For example, when running the example script found here:
>  http://scikit-learn.org/0.10/auto_examples/linear_model/plot_sgd_ols.html
> If I replace the line:
>   xmin, xmax = -5, 5
> with:
>   xmin, xmax = 0, 100
> then the regression fails (full traceback copied below).  If the range
> is set to (0, 50), the call does not produce an error, but leads to a
> line which clearly does not fit the data (intercept on order -2E30).
> Any ideas about what is going on here?
>   Jake
>
>  "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-i686.egg/sklearn/linear_model/stochastic_gradient.py",
> line 737, in fit
>    coef_init, intercept_init)
>  File
> "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-i686.egg/sklearn/linear_model/stochastic_gradient.py",
> line 672, in _partial_fit
>    self._fit_regressor(X, y, sample_weight, n_iter)
>  File
> "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-i686.egg/sklearn/linear_model/stochastic_gradient.py",
> line 786, in _fit_regressor
>    intercept_decay)
>  File "sgd_fast.pyx", line 423, in
> sklearn.linear_model.sgd_fast.plain_sgd
> (sklearn/linear_model/sgd_fast.c:6713)
> ValueError: floating-point under-/overflow occured.
>
>
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-- 
Peter Prettenhofer

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