sklearn GMM引发"ValueError:设置具有序列的数组元素".在稀疏矩阵上 [英] sklearn GMM raises "ValueError: setting an array element with a sequence." on sparse matrix

问题描述

我正在尝试将一组表示为稀疏密密矩阵X的数据点聚类.

I am attempting to cluster a set of data points that are represented as a sparse scipy matrix, X. That is,

>>> print type(X)
    <class 'scipy.sparse.csr.csr_matrix'>
>>> print X.shape
    (57, 1038)
>>> print X[0]
  (0, 223)  0.471313296962
  (0, 420)  0.621222153695
  (0, 1030) 0.442688836467
  (0, 124)  0.442688836467

但是，当我将此矩阵输入sklearn.mixture.GMM模型时，它会引发以下ValueError:

When I feed this matrix into an sklearn.mixture.GMM model, however, it raises the following ValueError:

 File "/Library/Python/2.7/site-packages/sklearn/mixture/gmm.py", line 423, in fit
      X = np.asarray(X, dtype=np.float)
 File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/core/numeric.py", line 235, in asarray
     return array(a, dtype, copy=False, order=order)
 ValueError: setting an array element with a sequence.

但是，我已经能够使sklearn.cluster.KMeans模型在相同的稀疏矩阵X上完美地工作.

However, I have been able to make the sklearn.cluster.KMeans model work perfectly on the same sparse matrix X.

其他一些希望有用的信息: scipy版本= 0.11.0，sklearn版本= 0.14.1

Some other hopefully useful info: scipy version = 0.11.0, sklearn version = 0.14.1

关于出什么问题的任何想法?预先感谢！

Any ideas on what is going wrong? Thanks in advance!

推荐答案

GMM不支持稀疏矩阵输入，而KMeans则支持.如果估算器支持稀疏矩阵，则始终在相关方法的文档字符串中明确指出.

GMMs don't support sparse matrix input, while KMeans does. If an estimator supports sparse matrices, this is always explicitly stated in the docstring for the relevant method.

这篇关于sklearn GMM引发"ValueError:设置具有序列的数组元素".在稀疏矩阵上的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！