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borchero avatar borchero commented on June 15, 2024 1

Hey @esrah-ap-niht. Unfortunately, full covariance matrices are currently not implemented. I'm in the process of refactoring the library though to make the interface even closer to sklearn's. I'll make sure to add it then :)

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groadabike avatar groadabike commented on June 15, 2024

Hi @esrah-ap-niht ,
Are you using diagonal covariance?

def __init__(self, num_components, num_features, covariance='diag'):

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esrah-ap-niht avatar esrah-ap-niht commented on June 15, 2024

@groadabike
No, I had gmm = GMM(num_components=20, num_features=test2.shape[1], covariance='spherical') specified. However, you are absolutely correct that the specification explains the shape of the matrix. I feel stupid I didn't catch that myself.

Thinking about this, the thread title should actually change to a feature request for a full covariance matrix option. Or if that's already implemented, knowing what text to use in the specification. I tried using "full" in the same style as Sklearn and received an error message.

image

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esrah-ap-niht avatar esrah-ap-niht commented on June 15, 2024

Thank you @borchero, I'll look forward to it. I'm using your code for research and would like to cite your work. Do you have a reference you'd like me to use? Otherwise I can use a generic reference along the lines of:

image

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borchero avatar borchero commented on June 15, 2024

Happy to see it being used in your research, @esrah-ap-niht ! :D unfortunately, there is no public work using the library, so the generic reference is definitely fine :) Thanks for asking!

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borchero avatar borchero commented on June 15, 2024

@esrah-ap-niht full covariances matrices are finally implemented :)

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