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www.aispace.org Inteligencia Artificial artificial intelligence

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Bayesian probability - Wikipedia, the free encyclopedia - 0 views

en.wikipedia.org/...Bayesian_probability Inteligencia Artificial artificial intelligence

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evaluate the probability of a hypothesis,
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n contrast to interpreting probability as the "frequency" or "propensity
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In the Bayesian view, a probability is assigned to a hypothesis, whereas under the frequentist view, a hypothesis is typically tested without being assigned a probability.
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the rules of Bayesian statistics can be justified by requirements of rationality and consistency and interpreted as an extension of logic
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According to the subjectivist view, probability quantifies a "personal belief".[3] Many modern machine learning methods are based on objectivist Bayesian principles
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For objectivists, probability objectively measures the plausibility of propositions, i.e. the probability of a proposition corresponds to a reasonable belief everyone
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or subjectivists, rationality and coherence constrain the probabilities a subject may have, but allow for substantial variation within those constraints.
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"inverse probability" (because it infers backwards from observations to parameters, or from effects to causes)
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"inverse probability" was largely supplanted by a collection of methods that came to be called frequentist statistics.[11]
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In the objectivist stream, the statistical analysis depends on only the model assumed and the data analysed.[12] No subjective decisions need to be involved. In contrast, "subjectivist" statisticians deny the possibility of fully objective analysis for the general case.
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frequentist statistics.
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several arguments, such as the Cox axioms, the Dutch book argument, arguments based on decision theory and de Finetti's theorem.
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Richard T. Cox showed that[6] Bayesian updating follows from several axioms, including two functional equations and a controversial hypothesis of differentiability.
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A Dutch book is made when a clever gambler places a set of bets that guarantee a profit, no matter what the outcome of the bets. If a bookmaker follows the rules of the Bayesian calculus in the construction of his odds, a Dutch book cannot be made
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every admissible statistical procedure is either a Bayesian procedure or a limit of Bayesian procedures.[19] Conversely, every Bayesian procedure is admissible.[20]
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his work demonstrates that Bayesian-probability propositions can be falsified, and so meet an empirical criterion of Charles S. Peirce, whose work inspired Ramsey. (This falsifiability-criterion was popularized by Karl Popper.[25][26])
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