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EM 算法是 Dempster,Laind,Rubin 于 1977 年提出的求参数极大似然估计的一种方法,它可以从非完整数据集中对参数进行 MLE 估计,是一种非常简单实用的学习算法。这种方法可以广泛地应用于处理缺损数据,截尾数据,带有讨厌数据等所谓的不完全数据(incomplete data)。需要weka的算法包支持。-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).
Update : 2025-02-17 Size : 9kb Publisher : zhangrui
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