10000 QDA may meet broken 2d array · Issue #4006 · scikit-learn/scikit-learn · GitHub
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MidoriYakumo opened this issue Dec 26, 2014 · 6 comments · Fixed by #4057
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QDA may meet broken 2d array #4006

MidoriYakumo opened this issue Dec 26, 2014 · 6 comments · Fixed by #4057
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0.16

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@MidoriYakumo
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>>> sklearn.__version__
'0.16-git'

For my dataset it gives:

  File "/usr/lib64/python3.4/site-packages/sklearn/qda.py", line 148, in _decision_function
    return (-0.5 * (norm2 + np.sum(np.log(self.scalings_), 1))
AttributeError: 'numpy.ndarray' object has no attribute 'log'

When

qda.py:134:         self.scalings_ = np.asarray(scalings)

It shows that scalings is a 2d array in shape of (0..23, 0..23, 0..23, 0..6)
@larsmans larsmans mentioned this issue Dec 27, 2014
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@agramfort
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close if it was fixed by #3755 I just merged.

@amueller
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amueller commented Jan 6, 2015

This could be caused by dtype='object'.

@amueller
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amueller commented Jan 6, 2015

@MidoriYakumo can you give us X.dtype for your data?

@amueller amueller mentioned this issue Jan 6, 2015
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@MidoriYakumo
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I did not store that data but it is true that bad shape caused this error, a normal 2d "array in array" can be automatically and safely converted by numpy, I think.

@MidoriYakumo
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Python 2.7.9 (default, Dec 13 2014, 18:02:08) [GCC] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
np>>a=np.array([1,2,3])
>>> b=np.array([1,2])
>>> c=np.array([a,a,b])
>>> c
array([array([1, 2, 3]), array([1, 2, 3]), array([1, 2])], dtype=object)
>>> np.log(c)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'numpy.ndarray' object has no attribute 'log'
>>> d=np.array([a,a,a])
>>> np.log(d)
array([[ 0.        ,  0.69314718,  
8000
1.09861229],
       [ 0.        ,  0.69314718,  1.09861229],
       [ 0.        ,  0.69314718,  1.09861229]])

@amueller amueller added the Bug label Jan 7, 2015
@amueller
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amueller commented Jan 7, 2015

Ok, I'm working on it in #4057.

@amueller amueller mentioned this issue Jan 7, 2015
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@amueller amueller added this to the 0.16 milestone Jan 16, 2015
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[MRG + 2] make check_array convert object to float. amueller/scikit-learn
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@agramfort @amueller @MidoriYakumo
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