| 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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| bayesian statistics |
Statistics which incorporate prior knowledge and accumulated experience into probability calculations.
출처: www.dmdsurveys.com/dmd_site3/terminology_pages/ter...
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| bay |
Sections into which the nave of a church is divided, generally by columns or pillars. Can be counted by following the longitudinal axis.
출처: www.viaoccitanacatalana.org/intro/glossario_ing.ht...
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| bay |
A recess or inlet in the shore of a sea or lake between two capes or headlands, not as large as a gulf but larger than a cove. See also bight.
출처: www.stripers247.com/glossary.htm
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| bay |
a small body of water set off from the main body; an inlet of the sea usually smaller than a gulf
출처: bonita.mbnms.nos.noaa.gov/Educate/teachercurriculu...
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