scikit-learn最近的邻居.kneighbors()on tfidf给出了ValueError:UPDATEIFCOPY base是只读的

时间:2017-11-06 11:36:16

标签: python machine-learning parallel-processing scikit-learn nearest-neighbor

我正在使用scikit-learn NearestNeighbors来查找最近的邻居,在人们维基数据上使用tfidf。

在我的.kneighbors()方法调用

res = neigh.kneighbors(obama_tfidf, return_distance=False)

Multiprocessing 模块抛出了以下异常:

ValueError: UPDATEIFCOPY base is read-only

我已在我的github location here上传了我的完整代码和示例数据(大小为80 MB)以供参考。

以下是错误列表的一部分:

---------------------------------------------------------------------------
JoblibValueError                          Traceback (most recent call last)
<ipython-input-12-dbcbed49b042> in <module>()
      1 obama_word_counts = count_vectorizer.transform(['obama'])
      2 obama_tfidf = tfidf_transformer.transform(obama_word_counts)
----> 3 res = neigh.kneighbors(obama_tfidf, return_distance=False)
      4 print res

/usr/local/lib/python2.7/dist-packages/sklearn/neighbors/base.pyc in kneighbors(self, X, n_neighbors, return_distance)
    355             if self.effective_metric_ == 'euclidean':
    356                 dist = pairwise_distances(X, self._fit_X, 'euclidean',
--> 357                                           n_jobs=n_jobs, squared=True)
    358             else:
    359                 dist = pairwise_distances(

/usr/local/lib/python2.7/dist-packages/sklearn/metrics/pairwise.pyc in pairwise_distances(X, Y, metric, n_jobs, **kwds)
   1245         func = partial(distance.cdist, metric=metric, **kwds)
   1246 
-> 1247     return _parallel_pairwise(X, Y, func, n_jobs, **kwds)
   1248 
   1249 

/usr/local/lib/python2.7/dist-packages/sklearn/metrics/pairwise.pyc in _parallel_pairwise(X, Y, func, n_jobs, **kwds)
   1094     ret = Parallel(n_jobs=n_jobs, verbose=0)(
   1095         fd(X, Y[s], **kwds)
-> 1096         for s in gen_even_slices(Y.shape[0], n_jobs))
   1097 
   1098     return np.hstack(ret)

/usr/local/lib/python2.7/dist-packages/sklearn/externals/joblib/parallel.pyc in __call__(self, iterable)
    787                 # consumption.
    788                 self._iterating = False
--> 789             self.retrieve()
    790             # Make sure that we get a last message telling us we are done
    791             elapsed_time = time.time() - self._start_time

/usr/local/lib/python2.7/dist-packages/sklearn/externals/joblib/parallel.pyc in retrieve(self)
    738                     exception = exception_type(report)
    739 
--> 740                     raise exception
    741 
    742     def __call__(self, iterable):

JoblibValueError: JoblibValueError

我无法粘贴整个多处理异常,因为它超出了S / O发布限制。

我在这里缺少什么?

1 个答案:

答案 0 :(得分:1)

n_jobs等于-1时,则将作业数设置为CPU核心数,如ref中所述。

当sklearn NN函数调用_parallel_pairwise(),然后尝试获取甚至切片时,会发生错误。

尝试将n_jobs设置为偶数,当然小于CPU核心数。

正如您已经提到的,您可以在n_jobs等于1的情况下运行此操作,这不会使代码并行化,从而不会暴露错误。