python - 值错误: array must not contain infs or NaNs during Biclustering

Question

我正在尝试对双聚类进行建模，但它失败了，因为它说数组包含 infs 和 nans，尽管我使用 pd.isnull(DataFile) 扫描了数组).sum()

 import pandas as pd
 import numpy as np
 from matplotlib import pyplot as plt
 from sklearn.datasets import samples_generator as sg
 from sklearn.cluster.bicluster import SpectralCoclustering
 from sklearn.metrics import consensus_score
 DataFile=pd.read_csv("DatafilledProp.csv",sep='\t')


 DataFile.drop(DataFile.columns[[0, 1]], axis=1, inplace=True)
 plt.matshow(DataFile.as_matrix(), cmap=plt.cm.Blues)
 plt.title("Original TransMapping")
 data, row_idx, col_idx = sg._shuffle(DataFile.as_matrix(), random_state=0)
 plt.matshow(data, cmap=plt.cm.Blues)
 plt.title("Shuffled dataset")
 plt.show()
 Features=DataFile.values
 model = SpectralCoclustering(n_clusters=10, random_state=0)
 model.fit(Features)

这是我得到的错误:

File "C:\Program Files (x86)\Microsoft Visual Studio 11.0\Common7\IDE\Extensio
ns\Microsoft\Python Tools for Visual Studio\2.1\visualstudio_py_util.py", line 1 06, in exec_file
exec_code(code, file, global_variables)
       File "C:\Program Files (x86)\Microsoft Visual Studio 11.0\Common7\IDE\Extensio
     ns\Microsoft\Python Tools for Visual Studio\2.1\visualstudio_py_util.py", line 8
     2, in exec_code
         exec(code_obj, global_variables)
       File "D:\ClusteringDemo\DataPreparation.py\DataPreparation.py\Model.py", line
     19, in <module>
         model.fit(Features)
       File "C:\Users\vinay.sawant\AppData\Local\Continuum\Anaconda\lib\site-packages
     \sklearn\cluster\bicluster\spectral.py", line 126, in fit
         self._fit(X)
       File "C:\Users\vinay.sawant\AppData\Local\Continuum\Anaconda\lib\site-packages
     \sklearn\cluster\bicluster\spectral.py", line 275, in _fit
         u, v = self._svd(normalized_data, n_sv, n_discard=1)
       File "C:\Users\vinay.sawant\AppData\Local\Continuum\Anaconda\lib\site-packages
     \sklearn\cluster\bicluster\spectral.py", line 139, in _svd
         **kwargs)
       File "C:\Users\vinay.sawant\AppData\Local\Continuum\Anaconda\lib\site-packages
     \sklearn\utils\extmath.py", line 299, in randomized_svd
         Q = randomized_range_finder(M, n_random, n_iter, random_state)
       File "C:\Users\vinay.sawant\AppData\Local\Continuum\Anaconda\lib\site-packages
     \sklearn\utils\extmath.py", line 226, in randomized_range_finder
         Q, R = linalg.qr(Y, mode='economic')
       File "C:\Users\vinay.sawant\AppData\Local\Continuum\Anaconda\lib\site-packages
     \scipy\linalg\decomp_qr.py", line 127, in qr
         a1 = numpy.asarray_chkfinite(a)
       File "C:\Users\vinay.sawant\AppData\Local\Continuum\Anaconda\lib\site-packages
     \numpy\lib\function_base.py", line 613, in asarray_chkfinite
         "array must not contain infs or NaNs")
     ValueError: array must not contain infs or NaNs
     Press any key to continue .

Answer 1

此问题已在这里得到解答:https://stackoverflow.com/a/42764378/2649309

It could be problem with PCA implementation in scikit-learn 0.18.1.

See a bug report https://github.com/scikit-learn/scikit-learn/issues/7568

Described workaround is to use PCA with svd_solver='full'. So try this code:

pipe = [('pca',PCA(whiten=True,svd_solver='full')),
   ('clf' ,lm)]

我能够通过此解决我的问题。