estimation-maximization algorithm
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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
Estimation theory — is a branch of statistics and signal processing that deals with estimating the values of parameters based on measured/empirical data. The parameters describe an underlying physical setting in such a way that the value of the parameters affects… … Wikipedia
Rasch model estimation — Various techniques are employed in order to estimate parameters of the Rasch model from matrices of response data. The most common approaches are methods of maximum likelihood estimation, such as joint and conditional maximum likelihood… … Wikipedia
Inside-outside algorithm — The inside outside algorithm is a way of re estimating production probabilities in a probabilistic context free grammar. It was introduced by James K. Baker in 1979 as a generalization of the forward backward algorithm for parameter estimation on … 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
Maximum a posteriori estimation — In Bayesian statistics, a maximum a posteriori probability (MAP) estimate is a mode of the posterior distribution. The MAP can be used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is closely related to… … 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
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
One-shot learning — is an object categorization problem of current research interest in computer vision. Whereas most machine learning based object categorization algorithms require training on hundreds or thousands of images and very large datasets, one shot… … Wikipedia
List of statistics topics — Please add any Wikipedia articles related to statistics that are not already on this list.The Related changes link in the margin of this page (below search) leads to a list of the most recent changes to the articles listed below. To see the most… … Wikipedia
List of mathematics articles (E) — NOTOC E E₇ E (mathematical constant) E function E₈ lattice E₈ manifold E∞ operad E7½ E8 investigation tool Earley parser Early stopping Earnshaw s theorem Earth mover s distance East Journal on Approximations Eastern Arabic numerals Easton s… … Wikipedia
