Bayesian Probability
Bayesian probability is a statistical interpretation of probability as a measure of the degree of belief, or subjective confidence, that an individual has in the occurrence of a particular event. It is based on Bayes' theorem, which describes the probability of an event based on prior knowledge or beliefs about related events. In data science, Bayesian probability is used to update prior beliefs about a hypothesis or model based on new data, resulting in a posterior probability distribution. This approach is particularly useful in situations where data is limited or uncertain, and can help to quantify the uncertainty associated with a particular prediction or decision.
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