Problem with GMM library from sklear.mixture?

Question

I want to run this example about 1D Gaussian Mixture Example: http://www.astroml.org/book_figures/chapter4/fig_GMM_1D.html
But I have this error all the time:

    from sklearn.mixture import GMM
ImportError: cannot import name 'GMM'

I tried to replace it by from sklearn.mixture import GaussianMixture but the code does not work, they do not have the same functionalities.

Thank you in advance.

Asked By: dina

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Source

Answer 1

The newer versions of scikit-learn don’t have that module. From looking at the versions it was deprecated in v 0.18 and removed in v 0.20. Here is the link to the OLD 0.18 module, which is the first instance i could find that shows a deprecation warning. https://scikit-learn.org/0.18/modules/generated/sklearn.mixture.GMM.html#sklearn.mixture.GMM if you want you can install an older version
pip install -Iv scikit-learn==0.15, or if you want to use the newer version, adapt the parameters of your GaussianMixture to reflect their new names (e.g. in GaussianMixture, max_iter is the number of iterations, instead of n_iter).

Answered By: Juan Carlos Ramirez

Answer 2

sklearn Gaussian Mixture implementation

Old (outdated, not supported in newer sklearn versions):

from sklearn.mixture import GMM     
model = GMM(n_components=3,covariance_type='full')

New and supported

from sklearn import mixture
model = mixture.GaussianMixture(n_components=3, covariance_type='full')

n_components default value is 1, choose what you want. That’s number of mixture components.

Answered By: Hrvoje

Answer 3

Use this instead

    from sklearn.mixture import GaussianMixture as GMM
    model=GMM(n_components=3,covariance_type='full')
    model.fit(X_iris)

This should solve your issue

Answered By: Akshay Raikar

Problem with GMM library from sklear.mixture?

Question:

Answers:

sklearn Gaussian Mixture implementation