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How does one do the equivalent of the following code with GaussianMixtures.jl?
import numpy as np from sklearn.mixture import GaussianMixture X = np.array([[1, 2], [1, 4], [1, 0], [10, 2], [10, 4], [10, 0]]) gm = GaussianMixture(n_components=2, random_state=0).fit(X) gm.predict([[0, 0], [12, 3]]) #prints "array([1, 0])"
Thanks in advance for any pointers :)
The text was updated successfully, but these errors were encountered:
I recall that I had included a PR providing such an interface, see scikitlearn.jl.
It might be that we need some better documentation, which currently is pretty poor anyways.
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How does one do the equivalent of the following code with GaussianMixtures.jl?
Thanks in advance for any pointers :)
The text was updated successfully, but these errors were encountered: