我在具有24GB内存的Windows 8 64位系统上运行Python 2.7(64位).在进行通常的拟合时Sklearn.linear_models.Ridge,代码运行正常.
问题:然而,当Sklearn.linear_models.RidgeCV(alphas=alphas)用于拟合时,我MemoryError在rr.fit(X_train, y_train)执行拟合程序的行上遇到下面显示的错误.
我该如何防止此错误?
代码段
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)
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错误
MemoryError Traceback (most recent call last)
<ipython-input-41-a433716e7179> in <module>()
1 # Fit Training set
----> 2 rr = fit(X_train, y_train)
<ipython-input-35-9650bd58e76c> 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, …Run Code Online (Sandbox Code Playgroud) 我的代码如下所示:
from sklearn.datasets import load_svmlight_files
import numpy as np
perm1 =np.random.permutation(25000)
perm2 = np.random.permutation(25000)
X_tr, y_tr, X_te, y_te = load_svmlight_files(("dir/file.feat", "dir/file.feat"))
#randomly shuffle data
X_train = X_tr[perm1,:].toarray()[:,0:2000]
y_train = y_tr[perm1]>5 #turn into binary problem
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代码工作正常,直到这里,但当我尝试将另一个对象转换为数组时,我的程序返回内存错误.
码:
X_test = X_te[perm2,:].toarray()[:,0:2000]
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错误:
---------------------------------------------------------------------------
MemoryError Traceback (most recent call last)
<ipython-input-7-31f5e4f6b00c> in <module>()
----> 1 X_test = X_test.toarray()
C:\Users\Asq\AppData\Local\Enthought\Canopy\User\lib\site-packages\scipy\sparse\compressed.pyc in toarray(self, order, out)
788 def toarray(self, order=None, out=None):
789 """See the docstring for `spmatrix.toarray`."""
--> 790 return self.tocoo(copy=False).toarray(order=order, out=out)
791
792 ##############################################################
C:\Users\Asq\AppData\Local\Enthought\Canopy\User\lib\site-packages\scipy\sparse\coo.pyc …Run Code Online (Sandbox Code Playgroud)