简单介绍
算法大鉴赏:高斯混合模型(Gaussian mixture model) - 知乎 (zhihu.com)
与k均值区别
最佳聚类实践:高斯混合模型(GMM) - 知乎 (zhihu.com)
GMM不需要对数据做标准化处理
Gaussian Mixture Modelling explicitly relaxes both the assumption of all clusters having the same variance, and the assumption of no correlation of features within a cluster, and that's why you don't need to standardise your features.
To be clear, the real advantage to using Gaussian Mixture Models is that your clusters don't have to be hyper-spherical and of the same radius. The fact that you also don't have to standardise your variables is just a nice bonus
Gaussian process regression (GPR)
算法包
sklearn.mixture.GaussianMixture — scikit-learn 1.1.2 documentation
2.1. Gaussian mixture models — scikit-learn 1.1.2 documentation