python - ImportError : cannot import name choice when importing sklearn. 混合物

Question

我正在使用 scikit learn 0.15.0。当我尝试导入 sklearn.mixture 时，我得到ImportError: 无法导入名称选择

有什么想法吗？

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In [1]: **from sklearn import mixture**

ImportError                               Traceback (most recent call last)
<ipython-input-1-05bc76cab98d> in <module>()
----> 1 from sklearn import mixture

/home/f/anaconda/lib/python2.7/site-packages/sklearn/mixture/__init__.py in <module>()
      3 """
      4
----> 5 from .gmm import sample_gaussian, log_multivariate_normal_density
      6 from .gmm import GMM, distribute_covar_matrix_to_match_covariance_type
      7 from .gmm import _validate_covars

/home/f/anaconda/lib/python2.7/site-packages/sklearn/mixture/gmm.py in <module>()
     16 from ..utils import check_random_state, deprecated
     17 from ..utils.extmath import logsumexp, pinvh
---> 18 from .. import cluster
     19
     20 from sklearn.externals.six.moves import zip

/home/f/anaconda/lib/python2.7/site-packages/sklearn/cluster/__init__.py in <module>()
      4 """
      5
----> 6 from .spectral import spectral_clustering, SpectralClustering
      7 from .mean_shift_ import mean_shift, MeanShift, estimate_bandwidth, \
      8     get_bin_seeds

/home/f/anaconda/lib/python2.7/site-packages/sklearn/cluster/spectral.py in <module>()
     16 from ..neighbors import kneighbors_graph
     17 from ..manifold import spectral_embedding
---> 18 from .k_means_ import k_means
     19
     20

/home/f/anaconda/lib/python2.7/site-packages/sklearn/cluster/k_means_.py in <module>()
     28 from ..utils import as_float_array
     29 from ..utils import gen_batches
---> 30 from ..utils.random import choice
     31 from ..externals.joblib import Parallel
     32 from ..externals.joblib import delayed

ImportError: cannot import name choice

Answer 1

from sklearn.mixture import GaussianMixture

使用它可以更具体地使用 .gmm，

和

from sklearn.cluster import KMeans

对于:

     16 from ..neighbors import kneighbors_graph
     17 from ..manifold import spectral_embedding
---> 18 from .k_means_ import k_means