There are quite a few Expectation Maximization based Gaussian mixture models. However, the models do not set any prior for mean and variance. I have implemented a 1D GMM inspired by Chris McCormick. Such a model can be helpful in cases where the data range is small and will prevent kernel overlap by restricting the kernels around the prior values.
引用格式
Rini (2024). Gaussian mixture model parameter estimation with prior hyper parameters (https://www.mathworks.com/matlabcentral/fileexchange/52775-gaussian-mixture-model-parameter-estimation-with-prior-hyper-parameters), MATLAB Central File Exchange. 检索时间: .
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参考作品: EM Algorithm for Gaussian Mixture Model (EM GMM), Expectation Maximization Algorithm with Gaussian Mixture Model
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1.0.0.0 |