Cognitive Computing in Business
Gibbs Sampling is a Markov Chain Monte Carlo (MCMC) algorithm used for obtaining a sequence of observations approximating the joint distribution of multiple random variables. This technique is particularly useful in probabilistic reasoning and Bayesian networks, as it allows for the generation of samples from complex distributions by iteratively sampling each variable conditioned on the current values of other variables, effectively managing dependencies among them.
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