Machine learningMachine learning
正则化高斯混合模型
正则化高斯混合模型（GMM）在期望最大化算法中向每个分量的协方差矩阵对角线添加一个小的正数常数，从而防止在数据稀疏、高维或包含近乎重复观测值时导致数值失败的奇异或近奇异矩阵。
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来源
- Fraley, C. & Raftery, A. E. (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association, 97(458), 611–631. DOI: 10.1198/016214502760047131 ↗
- Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Ch. 9). Springer. ISBN: 978-0-387-31073-2
如何引用本页
ScholarGate. (2026, June 3). Regularized Gaussian Mixture Model (Covariance-Regularized EM Clustering). ScholarGate. https://scholargate.app/zh/machine-learning/regularized-gaussian-mixture-model
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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