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Ok this is extremely weird, can someone run this code and see if it crashes with that error?

    import pandas  as pd
    import numpy as np
    from sklearn.covariance import MinCovDet

    clf=MinCovDet()

    dataF=np.array([0.5, 0.1, 0.1, 0.1, 0.957, 0.1, 0.1, 0.1, 0.4285, 0.1])

    manual=pd.DataFrame(data=dataF)
    clf.fit(manual)

If I change the array to this

# Working
dataF=np.array([0.5, 0.11, 0.1, 0.1, 0.957, 0.1, 0.1, 0.1, 0.4285, 0.1])

it runs fine. But it seems to crash with any array where there are too many of the same values. This array crashes as well.

# Not working
dataF = np.array([0.5, 0.3, 0.3, 0.3, 0.957, 0.3, 0.3, 0.3, 0.4285, 0.3])

I already checked for NANs and everything, there's nothing.

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    $\begingroup$ When I run your code, it gives me a Runtime Warning: divide by zero encountered in true_divide and another one RuntimeWarning: invalid value encountered in true_divide and so on. Working through the error message might be useful for finding the reason for this ValueError. $\endgroup$
    – So S
    Commented Oct 3, 2017 at 14:15

1 Answer 1

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Well, it seems to be an issue with the library, I opened an issue in gitHub

https://github.com/scikit-learn/scikit-learn/issues/9864

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