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etimología

Qué (quién) es Bayes risk - definición

ESTIMATOR OR DECISION RULE THAT MINIMIZES THE POSTERIOR EXPECTED VALUE OF A LOSS FUNCTION

Bayesian estimation; Bayesian estimate; Bayesian estimator; Bayes risk; Bayes estimation; Bayesian decision theory; Generalized Bayes estimator; Asymptotic efficiency (Bayes); Bayes action; Posterior mean; Bayesian risk

Bayes estimator

In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function (i.e.

https://en.wikipedia.org/wiki/Bayes_estimator

Bayes' theorem

$Figure 1: Using a frequency box to show <math>P(\text{User}\mid \text{Positive}) </math> visually by comparison of shaded areas$
$Figure 4: Tree diagram illustrating the beetle example. ''R, C, P'' and <math> \overline{P} </math> are the events rare, common, pattern and no pattern. Percentages in parentheses are calculated. Three independent values are given, so it is possible to calculate the inverse tree.$

THEOREM DESCRIBING THE PROBABILITY OF AN EVENT BASED ON PRIOR KNOWLEDGE OF CONDITIONS THAT MIGHT BE RELATED TO THE EVENT

Bayes Theorem; Bayes' rule; Bayes' Theorem; Bayes' formula; Bayes rule; Bayes' Rule; Bayes theorum; Bayes Rule; Bayes formula; Baye's rule; Bayes's Theorem; Bayes's theorem; Baye's Theorem; Bayes's rule; Bayes Theorum; Bay's rule; Bayes' theorem of subjective probability; Bayes' Law; Bayes Law; Baye's Law; Bayes' law; Pretest odds; Bayes theorem; Bayes’ Law; Bayes’ theorem; Bayes’s theorem; Bayes decision theory; Bayes' decision theory; Baye's theorem; Bayesian theorem; Bayes's law; Bayes-Price theorem; Bayes–Price theorem; Bayesian formula

In probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule), named after Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event. For example, if the risk of developing health problems is known to increase with age, Bayes' theorem allows the risk to an individual of a known age to be assessed more accurately (by conditioning it on their age) than simply assuming that the individual is typical of the population as a whole.

https://en.wikipedia.org/wiki/Bayes'_theorem

Bayes' theorem

$Figure 1: Using a frequency box to show <math>P(\text{User}\mid \text{Positive}) </math> visually by comparison of shaded areas$
$Figure 4: Tree diagram illustrating the beetle example. ''R, C, P'' and <math> \overline{P} </math> are the events rare, common, pattern and no pattern. Percentages in parentheses are calculated. Three independent values are given, so it is possible to calculate the inverse tree.$

THEOREM DESCRIBING THE PROBABILITY OF AN EVENT BASED ON PRIOR KNOWLEDGE OF CONDITIONS THAT MIGHT BE RELATED TO THE EVENT

Bayes Theorem; Bayes' rule; Bayes' Theorem; Bayes' formula; Bayes rule; Bayes' Rule; Bayes theorum; Bayes Rule; Bayes formula; Baye's rule; Bayes's Theorem; Bayes's theorem; Baye's Theorem; Bayes's rule; Bayes Theorum; Bay's rule; Bayes' theorem of subjective probability; Bayes' Law; Bayes Law; Baye's Law; Bayes' law; Pretest odds; Bayes theorem; Bayes’ Law; Bayes’ theorem; Bayes’s theorem; Bayes decision theory; Bayes' decision theory; Baye's theorem; Bayesian theorem; Bayes's law; Bayes-Price theorem; Bayes–Price theorem; Bayesian formula

¦ noun Statistics a theorem expressing the conditional probability of each of a set of possible causes for a given observed outcome in terms of the known probability of each cause and the conditional probability of the outcome of each cause.

Derivatives

Bayesian adjective

Origin

C19: named after the English mathematician Thomas Bayes.

Wikipedia

Bayes estimator

In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the posterior expectation of a utility function. An alternative way of formulating an estimator within Bayesian statistics is maximum a posteriori estimation.

https://en.wikipedia.org/wiki/Bayes estimator