kailugaji/gaussian_mixture_model_for_clustering

Gaussian Mixture Model for Clustering

Gaussian_Mixture_Model_for_Clustering

Gaussian Mixture Model for Clustering
Matlab code

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You can choose the methods of initialization and normalization.
The performance indices include ACC, ARI and ANMI.

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GMM algorithm:

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An Example for Iris

Run demo_data.m
The results of iris is:
Iteration 1, the number of iterations: 38, Accuary: 0.96666667
Iteration 2, the number of iterations: 38, Accuary: 0.96666667
Iteration 3, the number of iterations: 38, Accuary: 0.96666667
Iteration 4, the number of iterations: 38, Accuary: 0.96666667
Iteration 5, the number of iterations: 38, Accuary: 0.96666667
Iteration 6, the number of iterations: 38, Accuary: 0.96666667
Iteration 7, the number of iterations: 38, Accuary: 0.96666667
Iteration 8, the number of iterations: 38, Accuary: 0.96666667
Iteration 9, the number of iterations: 38, Accuary: 0.96666667
Iteration 10, the number of iterations: 38, Accuary: 0.96666667
The average iteration number of the algorithm is: 38.00
The average running time is: 0.11719
The average accuracy is: 0.96666667
The average rand index is: 0.95749441
The average normalized mutual information is: 0.89969459

Author of Code

Rongrong Wang (kailugaji)
My blog
2020/7/5