posterior probability


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Related to posterior probability: Prior probability

pos·te·ri·or prob·a·bil·i·ty

the best rational assessment of the probability of an outcome on the basis of established knowledge modified and brought up to date.
See also: prior probability, Bayes theorem.
References in periodicals archive ?
Compute the posterior probability [P.sup.(t)] {[[theta].sub.S] = 1 [a.sub.S] (t +1)) in the (t-1)th stage
In fact, the posterior probability of the target existence in each area is calculated to guide the resource allocation strategy, that is, we want to allocate more resource for the area in which the posterior probability of target existence [[??].sub.h]([y.sub.k]) is higher.
The model results show that "Group one" (the posterior probability is 0.43) and "Group two" (the posterior probability is 0.40) in "accident location" are likely to be associated with severe accidents, which could be attributed by the combination of higher average speed and larger speed dispersion.
The major idea of MLA is to generate a mechanism where query contents have as similar posterior probability as possible in each report.
According to the values of the posterior probability in Table 1, the presence of defects in the motor-pump is mainly caused by event M51.which summarizes the out of balance (M51) defect is the most likely source to stop the motor-pump.
During multilabel prediction, inferring the best set of labels for an unlabeled prescription at test time is more complex: it involves assessing all function label assignments and returning the assignment that has the highest posterior probability. However, the issue is not so simple, since there are [2.sup.K] possible function label assignments.
The probability results for two reservoir collapses for the various combinations of typical cases, and the posterior probability results, are shown in Table 10 and Figure 8.
The mode with the highest posterior probability can be determined as the underlying mode based on the maximum a posteriori (MAP) principle, and the related abnormality is generally regarded as the fault source.
According to the formula of Bayes' conditional probability, the posterior probability for CI is:
This linear discriminant model enables biologists to obtain the posterior probability that a harvested animal is from a given age class from its eye lens dry mass (Supplementary material Appendix 4 Table A2).
The proposed method uses particle filter method to estimate the joint posterior probability of motion and identity variables.
In practical pattern recognition problems, it may be very useful to obtain the posterior probability for the membership of an input in a particular class.

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