Gaussian Mixture Models and the EM algorithm汇总

Gaussian Mixture Models and the EM algorithm汇总

作者:凯鲁嘎吉 - 博客园 http://www.cnblogs.com/kailugaji/

1. 漫谈 Clustering (3): Gaussian Mixture Model « Free Mind

http://blog.pluskid.org/?p=39

2. Regularized Gaussian Covariance Estimation

http://freemind.pluskid.org/machine-learning/regularized-gaussian-covariance-estimation/

3. EM算法(Expectation Maximization) - 文墨 - 博客园

http://www.cnblogs.com/sparkwen/p/3199728.html

4. (EM算法)The EM Algorithm - JerryLead - 博客园

http://www.cnblogs.com/jerrylead/archive/2011/04/06/2006936.html

5. 从最大似然到EM算法浅解 - zouxy09的专栏 - CSDN博客

https://blog.csdn.net/zouxy09/article/details/8537620

6. 混合模型初探 - Andrew.Hann - 博客园

http://www.cnblogs.com/LittleHann/p/8446491.html

7. 高斯混合模型(GMM)参数优化及matlab实现_Amy_blog_新浪博客

http://blog.sina.com.cn/s/blog_65956f180100u5zt.html

8. 如何通俗理解EM算法 - 结构之法 算法之道 - CSDN博客

https://blog.csdn.net/v_JULY_v/article/details/81708386

9. 深度理解高斯混合模型(GMM)_用户2741655102_新浪博客

http://blog.sina.com.cn/s/blog_a36a563e0102y2ec.html

10. 高斯混合模型(GMM)及其EM算法的理解 - 小平子的专栏 - CSDN博客

https://blog.csdn.net/jinping_shi/article/details/59613054

笔记:正态变量的线性组合还是正态变量,而正态分布的线性组合可以逼近任意分布。

参考文献:Bishop C M , Bishop C , Bishop C . Pattern Recognition and Machine Learning (Information Science and Statistics)[M]. Springer-Verlag New York, Inc. 2006.

转载于:https://www.cnblogs.com/kailugaji/p/10405072.html

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