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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.
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The simplest way to initiate the GMM is to pick numClusters data points at random as mode means, initialize the individual covariances as the covariance of the data, and assign equa prior probabilities to the modes. This is the default initialization method used by vl_gmm .
A Gaussian mixture model (GMM) attempts to find a mixture of multi-dimensional Gaussian probability distributions that best model any input dataset. In the simplest case, GMMs can be used for finding clusters in the same manner as k-means: from sklearn.mixture import GMM gmm = GMM(n_components=4). fit(X) labels = gmm.
At its simplest, GMM is also a type of clustering algorithm. As its name implies, each cluster is modelled according to a different Gaussian distribution. This flexible and probabilistic approach to modelling the data means that rather than having hard assignments into clusters like k-means, we have soft assignments.
This class allows for easy evaluation of, sampling from, and maximum-likelihood estimation of the parameters of a GMM distribution. Initializes parameters such that every mixture component has zero mean and identity covariance.
GaussianMixture is designed to fit a Gaussian Mixture and this is for that reason that it doesn't check that np.sum (weights) = 1, ... This issue is linked to #7701 : I think what people want is a sample function outside GaussianMixture.
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.
Old (outdated, not supported in newer sklearn versions):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.
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