Hi everyone,
I am trying to use the SGDRegressor to solve for a sparse set of
linear equations. I am getting an under/over-flow error (see below).
Running master from github from this morning on Fedora 14.
Any ideas?
Thanks!
Ariel
In [30]: X
Out[30]:
<533100x18788 sparse matrix of type '<type 'numpy.float64'>'
with 52124700 stored elements in Compressed Sparse Column format>
In [31]: y
Out[31]: array([ 4.1 , 42.1 , 14.1 , ..., 11.82, -11.18, 25.82])
In [32]: y.shape
Out[32]: (533100,)
In [33]: from sklearn.linear_model import SGDRegressor as SGD
In [34]: S1 = SGD()
In [35]: S1.fit(X,y)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/white/u6/arokem/<ipython-input-35-1ebf5d8bf9f4> in <module>()
----> 1 S1.fit(X,y)
/home/arokem/usr/local/lib64/python2.7/site-packages/scikit_learn-0.11_git-py2.7-linux-x86_64.egg/sklearn/linear_model/stochastic_gradient.pyc
in fit(self, X, y, coef_init, intercept_init, sample_weight)
705
706 return self._partial_fit(X, y, self.n_iter, sample_weight,
--> 707 coef_init, intercept_init)
708
709 def decision_function(self, X):
/home/arokem/usr/local/lib64/python2.7/site-packages/scikit_learn-0.11_git-py2.7-linux-x86_64.egg/sklearn/linear_model/stochastic_gradient.pyc
in _partial_fit(self, X, y, n_iter, sample_weight, coef_init,
intercept_init)
640 coef_init, intercept_init)
641
--> 642 self._fit_regressor(X, y, sample_weight, n_iter)
643
644 self.t_ += n_iter * n_samples
/home/arokem/usr/local/lib64/python2.7/site-packages/scikit_learn-0.11_git-py2.7-linux-x86_64.egg/sklearn/linear_model/stochastic_gradient.pyc
in _fit_regressor(self, X, y, sample_weight, n_iter)
754 self.learning_rate_code,
755 self.eta0,
self.power_t, self.t_,
--> 756 intercept_decay)
757
758 self.intercept_ = np.atleast_1d(intercept)
/home/arokem/usr/local/lib64/python2.7/site-packages/scikit_learn-0.11_git-py2.7-linux-x86_64.egg/sklearn/linear_model/sgd_fast.so
in sklearn.linear_model.sgd_fast.plain_sgd
(sklearn/linear_model/sgd_fast.c:6164)()
ValueError: floating-point under-/overflow occured.
------------------------------------------------------------------------------
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