| Bayes' theorem |
(statistics) a theorem describing how the conditional probability of a set of possible causes for a given observed event can be computed from knowledge of the probability of each cause and the conditional probability of the outcome of each cause
출처: wordnet.princeton.edu/perl/webwn
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| Bayes' theorem |
A theorem (formula) that is used to compute posterior probabilities by revising prior probabilities. (page 784)
출처: highered.mcgraw-hill.com/sites/0072470267/student_...
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| Bayes' theorem |
SEE: Bayes' theorem..
출처:
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| Bayes' theorem |
A means to update the model parameter probability distributions based on data. Since p(MD) = p(M|D) p(D) = p(M) p(D|M), p(M|D) = p(M) p(D|M) / p(D). This is Bayes' Theorem. Usually, M represents the model parameters, D represents the data, and the | symbol indicates a statement of conditional probability. Here, p(M) are the a priori probabilities on the model parameters, p(D|M) is the likelihood, and p(D) is a normalizing factor.
출처: hea-www.harvard.edu/AstroStat/statjargon.html
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