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Bayesian Machine Learning
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Author(s): Eitel J.M. Lauria (Marist College, USA)
Copyright: 2005
Pages: 7
Source title:
Encyclopedia of Information Science and Technology
Source Author(s)/Editor(s): Mehdi Khosrow-Pour (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-553-5.ch043
ISBN13: 9781591405535
ISBN10: 159140553X
EISBN13: 9781591407942
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Abstract
Bayesian methods provide a probabilistic approach to machine learning. The Bayesian framework allows us to make inferences from data using probability models for values we observe and about which we want to draw some hypotheses. Bayes theorem provides the means of calculating the probability of a hypothesis (posterior probability) based on its prior probability, the probability of the observations and the likelihood that the observational data fit the hypothesis.
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