我在具有24GB內存的Windows 8 64位系統上運行Python 2.7(64位).在進行通常的Sklearn.linear_models.Ridge的擬合時,代碼運行正常.

問題：但是當使用Sklearn.linear_models.RidgeCV(alphas = alphas)進行擬合時,我會遇到執行擬合過程的rr.fit(X_train,y_train)行下面顯示的MemoryError錯誤.

如何防止此錯誤？

代碼段

def fit(X_train, y_train):

alphas = [1e-3, 1e-2, 1e-1, 1e0, 1e1]

rr = RidgeCV(alphas=alphas)

rr.fit(X_train, y_train)

return rr

rr = fit(X_train, y_train)

錯誤

MemoryError Traceback (most recent call last)

in ()

1 # Fit Training set

----> 2 rr = fit(X_train, y_train)

in fit(X_train, y_train)

3

4 rr = RidgeCV(alphas=alphas)

----> 5 rr.fit(X_train, y_train)

6

7 return rr

C:\Python27\lib\site-packages\sklearn\linear_model\ridge.pyc in fit(self, X, y, sample_weight)

696 gcv_mode=self.gcv_mode,

697 store_cv_values=self.store_cv_values)

--> 698 estimator.fit(X, y, sample_weight=sample_weight)

699 self.alpha_ = estimator.alpha_

700 if self.store_cv_values:

C:\Python27\lib\site-packages\sklearn\linear_model\ridge.pyc in fit(self, X, y, sample_weight)

608 raise ValueError('bad gcv_mode "%s"' % gcv_mode)

609

--> 610 v, Q, QT_y = _pre_compute(X, y)

611 n_y = 1 if len(y.shape) == 1 else y.shape[1]

612 cv_values = np.zeros((n_samples * n_y, len(self.alphas)))

C:\Python27\lib\site-packages\sklearn\linear_model\ridge.pyc in _pre_compute_svd(self, X, y)

531 def _pre_compute_svd(self, X, y):

532 if sparse.issparse(X) and hasattr(X, 'toarray'):

--> 533 X = X.toarray()

534 U, s, _ = np.linalg.svd(X, full_matrices=0)

535 v = s ** 2

C:\Python27\lib\site-packages\scipy\sparse\compressed.pyc in toarray(self, order, out)

559 def toarray(self, order=None, out=None):

560 """See the docstring for `spmatrix.toarray`."""

--> 561 return self.tocoo(copy=False).toarray(order=order, out=out)

562

563 ##############################################################

C:\Python27\lib\site-packages\scipy\sparse\coo.pyc in toarray(self, order, out)

236 def toarray(self, order=None, out=None):

237 """See the docstring for `spmatrix.toarray`."""

--> 238 B = self._process_toarray_args(order, out)

239 fortran = int(B.flags.f_contiguous)

240 if not fortran and not B.flags.c_contiguous:

C:\Python27\lib\site-packages\scipy\sparse\base.pyc in _process_toarray_args(self, order, out)

633 return out

634 else:

--> 635 return np.zeros(self.shape, dtype=self.dtype, order=order)

636

637

MemoryError:

碼

print type(X_train)

print X_train.shape

結果

(183576, 101507)

總結

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