Description: EM algorithm is Dempster, Laind, Rubin in 1977 for the parameters proposed by maximum likelihood estimation of a method, it can focus from non-complete data MLE of the parameters estimated, is a very simple and practical learning algorithm. This method can be widely applied to deal with defect data, censored data, with data such as the so-called hate incomplete data (incomplete data).
- [gaussianSrc] - The EM algorithm is short for Expectatio
- [ppkd] - based on finite Gaussian mixture model o
- [ML_and_MAP] - Maximum Likelihood (ML) criteria and max
- [RPEM_Source_Code] - EM algorithm, based on the expectation m
- [polya_fit] - This is a based on the Polya distributio
- [EM] - Detailed EM algorithm! ! Detailed EM alg
- [em_ghmm] - EM algorithm, used to estimate the param
- [EM_Introduction] - EM+AlgorithmEM+AlgorithmEM+AlgorithmEM+A
- [EM_WellingsNote] - EM Algorithm Max Welling
- [EM(1020B)] - Expectation-maximization algorithm
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115157702EM.java.tar
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