Bayes' rule - определение. Что такое Bayes' rule
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Что (кто) такое Bayes' rule - определение

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
  • Figure 1: Using a frequency box to show <math>P(\text{User}\mid \text{Positive}) </math> visually by comparison of shaded areas
  • function]] of ''x'' and ''y''.
  • Figure 2: A geometric visualisation of Bayes' theorem.
  • 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.
  • tree diagrams]].
  • Figure 6: A way to conceptualize event spaces generated by continuous random variables X and Y.

Bayes' theorem         
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.
Bayes' theorem         
¦ 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.
Naive Bayes classifier         
CLASSIFICATION ALGORITHM
Naive Bayesian classifier; Naive Bayes; Idiot's Bayes; Naive Bayesian classification; Naïve Bayesian classifier; Naïve Bayes; Naïve Bayes classifier; Naïve Bayesian classification; Naive-Bayes; Naive bayes classifier; Naive bayes; Idiot Bayes; Idiot Bayes Model; Naive bayes model; Baysian classifier; Bayesian classification; Bayesian Classifiers; Naive Bayesian Classification; Gaussian Naive Bayes; Multinomial Naive Bayes; Gaussian naive Bayes
In statistics, naive Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong (naive) independence assumptions between the features (see Bayes classifier). They are among the simplest Bayesian network models, but coupled with kernel density estimation, they can achieve high accuracy levels.

Википедия

Bayes' theorem

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 relative to their age, rather than simply assuming that the individual is typical of the population as a whole.

One of the many applications of Bayes' theorem is Bayesian inference, a particular approach to statistical inference. When applied, the probabilities involved in the theorem may have different probability interpretations. With Bayesian probability interpretation, the theorem expresses how a degree of belief, expressed as a probability, should rationally change to account for the availability of related evidence. Bayesian inference is fundamental to Bayesian statistics, being considered by one authority as; "to the theory of probability what Pythagoras's theorem is to geometry."