>
> It may come from the fact that np.dot(X, X.T) is not invertible.
>
I meant, of course, np.dot(X.T, X).
Would you look at the eigenvalues of this thing please?
On Thu, Jun 28, 2012 at 10:33 AM, Virgile Fritsch <[email protected]
> wrote:
> Hi,
>
> It may come from the fact that np.dot(X, X.T) is not invertible.
> Is it possible that two (or more) features are correlated? Or that one (or
> more) features have a 0 variance?
> If yes, try to remove those features.
>
> Let us know if you think this could be the reason why it fails.
>
> Virgile
>
>
> On Thu, Jun 28, 2012 at 1:08 AM, ert <[email protected]> wrote:
>
>> Hi,
>>
>> I am trying to use EllipticEnvelope for outlier detection but it results
>> in an error when trying to use the m.fit(X) function (stacktrace below).
>> Here
>> m = EllipticEnvelope(contamination=0.1)
>>
>> X.shape gives output
>> (731, 22)
>> X is not a sparse matrix.
>>
>> Initially, I thought there was some prob with my X, however
>> m = OneClassSVM()
>> m.fit(X)
>> runs fine without any errors. I am not sure if these are related.
>> Any idea what could be causing this?
>>
>> StackTrace (note 'instances' is a list of lists):-
>> Traceback (most recent call last):
>> File "create_classifier_new.py", line 274, in <module>
>> m.fit(numpy.array(instances))
>> File
>> "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-x86_64.egg/sklearn/covariance/outlier_detection.py",
>> line 176, in fit
>> MinCovDet.fit(self, X)
>> File
>> "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-x86_64.egg/sklearn/covariance/robust_covariance.py",
>> line 513, in fit
>> random_state=self.random_state)
>> File
>> "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-x86_64.egg/sklearn/covariance/robust_covariance.py",
>> line 360, in fast_mcd
>> random_state=random_state)
>> File
>> "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-x86_64.egg/sklearn/covariance/robust_covariance.py",
>> line 228, in select_candidates
>> random_state=random_state))
>> File
>> "/usr/local/lib/python2.6/dist-packages/scikit_learn-0.12_git-py2.6-linux-x86_64.egg/sklearn/covariance/robust_covariance.py",
>> line 120, in c_step
>> if np.allclose(det, previous_det):
>> File "/usr/lib/python2.6/dist-packages/numpy/core/numeric.py", line
>> 1671, in allclose
>> if not all(x[xinf] == y[xinf]):
>> IndexError: 0-d arrays can't be indexed
>>
>>
>> Thanks
>>
>>
>>
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