Examples of using Bayesian in English and their translations into Slovak
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Bayesian Decision Theory.
Pronounce Bayesian in English.
Bayesian models are predictive.
Be able to apply Bayesian statistical methods.
Bayesian models are commonly used.
Important publications in Bayesian statistics.
Bayesian, and we will go into that more.
Brief introduction to Bayesian statistics.
Bayesian analysis does not replace that.
What happens at this point, from a Bayesian perspective?
This will teach the Bayesian filter that this message is not SPAM.
Provides a concise introduction to Bayesian statistics.
Applications of Bayesian Decision Theory to Sequential Mastery Testing.
The most widely used one is the Bayesian filtering.
Using Bayesian Decision Theory to Design a Computerized Mastery Test.
We carried out two Bayesian hypothesis tests.
Variational free energy,a construct from information theory that is used in variational Bayesian methods.
Adaptive Testing: A Bayesian Procedure for the Efficient Measurement of Ability.
Consider Warren's argument from a Bayesian perspective.
For a true Bayesian, information would never have negative expected utility.
And what it means is we really are Bayesian inference machines.
For a true Bayesian, it is impossible to seek evidence that confirms a theory.
This talk will give a friendly introduction to Bayesian statistics.
This package implements a fast Bayesian spam filter along the lines suggested by Paul Graham in his article"A Plan For Spam".
Of course,the human brain is too slow to make explicit Bayesian calculations all day.
SpamBayes is a Bayesian spam filter written in Python which uses techniques laid out by Paul Graham in his essay"A Plan for Spam".
CRM114 is not just another drop-in spam-filtering system; its Sparse Binary Polynomial Hashing methodsgive it the power to develop highly accurate Bayesian filters on very little training.
One of the primary inspirations for Bayesian networks was noticing the problem of double-counting evidence if inference resonates between an effect and a cause.
Recently, careful analysis of the Bayesian classification problem has shown that there are some theoretical reasons for the apparently unreasonable efficacy of naive Bayes classifiers.
A naive Bayes classifier is a term in Bayesian statistics dealing with a simple probabilistic classifier based on applying Bayes' theorem with strong(naive) independence assumptions.