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<p>请参考以下地址的笔记本</p>
<p><a href="http://nbviewer.ipython.org/github/justmarkham/gadsdc1/blob/master/logistic_assignment/kevin_logistic_sklearn.ipynb" rel="nofollow noreferrer">LogisticRegression</a></p>
<p>这部分代码</p>
<pre><code>scores = cross_val_score(LogisticRegression(), X, y, scoring='accuracy', cv=10)
print scores
print scores.mean()
</code></pre>
<p>在Windows764位计算机中生成以下错误</p>
<pre><code>---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-37-4a10affe67c7> in <module>()
1 # evaluate the model using 10-fold cross-validation
----> 2 scores = cross_val_score(LogisticRegression(), X, y, scoring='accuracy', cv=10)
3 print scores
4 print scores.mean()
C:\Python27\lib\site-packages\sklearn\cross_validation.pyc in cross_val_score(estimator, X, y, scoring, cv, n_jobs, verbose, fit_params, score_func, pre_dispatch)
1140 allow_nans=True, allow_nd=True)
1141
-> 1142 cv = _check_cv(cv, X, y, classifier=is_classifier(estimator))
1143 scorer = check_scoring(estimator, score_func=score_func, scoring=scoring)
1144 # We clone the estimator to make sure that all the folds are
C:\Python27\lib\site-packages\sklearn\cross_validation.pyc in _check_cv(cv, X, y, classifier, warn_mask)
1366 if classifier:
1367 if type_of_target(y) in ['binary', 'multiclass']:
-> 1368 cv = StratifiedKFold(y, cv, indices=needs_indices)
1369 else:
1370 cv = KFold(_num_samples(y), cv, indices=needs_indices)
C:\Python27\lib\site-packages\sklearn\cross_validation.pyc in __init__(self, y, n_folds, indices, shuffle, random_state)
428 for test_fold_idx, per_label_splits in enumerate(zip(*per_label_cvs)):
429 for label, (_, test_split) in zip(unique_labels, per_label_splits):
--> 430 label_test_folds = test_folds[y == label]
431 # the test split can be too big because we used
432 # KFold(max(c, self.n_folds), self.n_folds) instead of
IndexError: too many indices for array
</code></pre>
<p>我正在使用scikit.learn 0.15.2,建议<a href="https://stackoverflow.com/questions/24236309/multilabel-grid-search-in-scikitlearn">here</a>这可能是Windows7 64位计算机的一个特定问题。</p>
<p>=update=update=update=</p>
<p>我发现下面的代码确实有效</p>
<pre><code> from sklearn.cross_validation import KFold
cv = KFold(X.shape[0], 10, shuffle=True, random_state=33)
scores = cross_val_score(LogisticRegression(), X, y, scoring='accuracy', cv=cv)
print scores
</code></pre>
<p>=update 2=</p>
<p>似乎由于某些包更新,我无法再在我的计算机上重现此类错误。如果您在Windows764位计算机上遇到同样的问题,请告诉我。</p>