Examples of using Bayesian in English and their translations into Serbian
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subjective currents in Bayesian practice.
If a bookmaker follows the rules of the Bayesian calculus in the construction of his odds,
This extended view allows the application of Bayesian techniques to SVMs,
This kind of interpretation is often called"Bayesian" because it assumes the writer is also incorporating a prior probability distribution of possible amounts of money in the two envelopes in the switching argument.
The Bayesian interpretation of probability can be seen as an extension of propositional logic that enables reasoning with hypotheses,[4]
In Bayesian data, probability could be assigned to a theory that may differ from 0 or 1, if the truth value is not certain.
The Bayesian interpretation of probability can be seen as an extension of logic that enables reasoning with propositions,
In Bayesian statistics, a probability can be assigned to a hypothesis that can differ from 0 or 1 if the truth value is uncertain.
The Bayesian interpretation of probability can be seen as an extension of logic that enables reasoning with propositions,
In Bayesian statistics, a probability can be assigned to a hypothesis that can differ from 0 or 1 if the true value is uncertain.
The Bayesian interpretation of probability could be viewed as an expansion of propositional logic that permits reasoning with theories,
published in their seminal work the first application of genetic type algorithm in Bayesian statistical inference.
The term Bayesian derives from the 18th century mathematician
e.g. Bayesian networks, Markov random fields
Causal network- a Bayesian network with an explicit requirement that the relationships be causal Structural equation modeling- a statistical technique for testing
A decision-theoretic justification of the use of Bayesian inference(and hence of Bayesian probabilities) was given by Abraham Wald,
For instance, a Bayesian network represents a system of probabilistic events as vertices in a directed acyclic graph,
Thus, for every decision rule, either the rule may be reformulated as a Bayesian procedure(or a limit of a sequence of such), or there is a
including aspect structuring[33] and the Bayesian semiparametric approach.[34]
propensity of some phenomenon, Bayesian probability is a quantity that we assign for the purpose of representing a state of knowledge,[1]