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conditional density

См. также в других словарях:

  • Density estimation — In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to… …   Wikipedia

  • Conditional probability distribution — Given two jointly distributed random variables X and Y, the conditional probability distribution of Y given X is the probability distribution of Y when X is known to be a particular value. If the conditional distribution of Y given X is a… …   Wikipedia

  • Conditional expectation — In probability theory, a conditional expectation (also known as conditional expected value or conditional mean) is the expected value of a real random variable with respect to a conditional probability distribution. The concept of conditional… …   Wikipedia

  • Conditional probability — The actual probability of an event A may in many circumstances differ from its original probability, because new information is available, in particular the information that an other event B has occurred. Intuition prescribes that the still… …   Wikipedia

  • Marginal conditional stochastic dominance — In finance, marginal conditional stochastic dominance is a condition under which a portfolio can be improved in the eyes of all risk averse investors by incrementally moving funds out of one asset (or one sub group of the portfolio s assets) and… …   Wikipedia

  • Conditioning (probability) — Beliefs depend on the available information. This idea is formalized in probability theory by conditioning. Conditional probabilities, conditional expectations and conditional distributions are treated on three levels: discrete probabilities,… …   Wikipedia

  • Borel's paradox — (sometimes known as the Borel Kolmogorov paradox) is a paradox of probability theory relating to conditional probability density functions. The paradox lies in fact that, contrary to intuition, conditional probability density functions are not… …   Wikipedia

  • Linear classifier — In the field of machine learning, the goal of classification is to group items that have similar feature values, into groups. A linear classifier achieves this by making a classification decision based on the value of the linear combination of… …   Wikipedia

  • Clasificador lineal — En el campo del aprendizaje automático, el objetivo del aprendizaje supervisado es usar las características de un objeto para identificar a qué clase (o grupo) pertenece. Un clasificador lineal logra esto tomando una decisión de clasificación… …   Wikipedia Español

  • Errors-in-variables models — In statistics and econometrics, errors in variables models or measurement errors models are regression models that account for measurement errors in the independent variables. In contrast, standard regression models assume that those regressors… …   Wikipedia

  • Generative model — In statistics, a generative model is a model for randomly generating observed data, typically given some hidden parameters. It specifies a joint probability distribution over observation and label sequences. Generative models are used in machine… …   Wikipedia

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