Expectation Maximization

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• Expectation-maximization algorithm — An expectation maximization (EM) algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an… …   Wikipedia

• Expectation-Maximization-Algorithmus — Der Expectation Maximization Algorithmus (kurz EM Algorithmus, selten auch Estimation Maximization Algorithmus) ist ein Algorithmus der mathematischen Statistik. Der EM Algorithmus wird vorrangig zur Ballungsanalyse verwendet (Siehe hierzu den… …   Deutsch Wikipedia

• Expectation-Maximization — Algorithme espérance maximisation L algorithme espérance maximisation (en anglais Expectation maximisation algorithm, souvent abrégé EM), proposé par Dempster et al. (1977), est une classe d algorithmes qui permettent de trouver le maximum de… …   Wikipédia en Français

• Ordered subset expectation maximization — This article is about an algorithm. For Israeli food corporation, see Osem (company). In mathematical optimization, the ordered subset expectation maximization (OSEM) method is an iterative method that is used in computed tomography. In… …   Wikipedia

• Maximization — or maximisation can refer to: Maximization in the sense of exaggeration Entropy maximization Maximization (economics) Profit maximization Utility maximization problem Budget maximizing model Shareholder value maximization Optimization… …   Wikipedia

• E-M — expectation maximization …   Medical dictionary

• E-M — • expectation maximization …   Dictionary of medical acronyms & abbreviations

• Mixture model — See also: Mixture distribution In statistics, a mixture model is a probabilistic model for representing the presence of sub populations within an overall population, without requiring that an observed data set should identify the sub population… …   Wikipedia

• Per Martin-Löf — in 2004 Born May 8, 1942 (194 …   Wikipedia

• k-means clustering — In statistics and data mining, k means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results into a partitioning of… …   Wikipedia