a prior probability造句

例句与造句

1. As you say, having a prior probability distribution is key.
2. The language acts as a prior probability.
3. A particularly important application of Dirichlet processes is as a prior probability distribution in infinite mixture models.
4. Probabilities before an inference are known as prior probabilities, and probabilities after are known as posterior probabilities.
5. This requires that either the signal statistics is known or a prior probability for the signal can be specified.
6. It's difficult to find a prior probability in a sentence. 用a prior probability造句挺难的
7. However, this does not mean the substring's absence is " impossible ", despite the absence having a prior probability of 0.
8. As shown in the next section, when using this expression as a prior probability times the likelihood in Bayes theorem, the posterior probability turns out to be a beta distribution.
9. In Bayesian statistics, the problem arises at that of deciding on a prior probability for the outcome in question ( or when considering multiple outcomes, a prior probability distribution ).
10. In Bayesian statistics, the problem arises at that of deciding on a prior probability for the outcome in question ( or when considering multiple outcomes, a prior probability distribution ).
11. In fact, " any " particular infinite sequence the immortal monkey types will have " had " a prior probability of 0, even though the monkey must type something.
12. 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.
13. This doesn't sound right, as the doctor must have taken other information, such as the symptoms, age and sex of the patient into consideration, when assigning a prior probability.
14. This contrasts with the Bayesian approach, which requires that the hypothesis be assigned a prior probability, which is revised in the light of the observed data to obtain the final probability of the hypothesis.
15. Bayesian inference provides a method for updating the probability that a hypothesis is true when presented with some evidence, but it requires a prior probability that the hypothesis is true before the evidence is presented.
16. Furthermore, Bayes'rule can be applied iteratively : after observing some evidence, the resulting posterior probability can then be treated as a prior probability, and a new posterior probability computed from new evidence.
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