Unobserved Variables

Some articles on unobserved variables, variables:

Bayesian Network - Inference and Learning - Parameter Learning
... probability) is often complex when there are unobserved variables ... expectation-maximization algorithm which alternates computing expected values of the unobserved variables conditional on observed data, with maximizing the complete likelihood (or posterior) assuming that previously ... A more fully Bayesian approach to parameters is to treat parameters as additional unobserved variables and to compute a full posterior distribution over all nodes conditional upon observed data, then to integrate ...
Variational Bayesian Methods
... models consisting of observed variables (usually termed "data") as well as unknown parameters and latent variables, with various sorts of relationships among the three types of random variables, as ... inference, the parameters and latent variables are grouped together as "unobserved variables" ... an analytical approximation to the posterior probability of the unobserved variables, in order to do statistical inference over these variables ...

Famous quotes containing the word variables:

    Science is feasible when the variables are few and can be enumerated; when their combinations are distinct and clear. We are tending toward the condition of science and aspiring to do it. The artist works out his own formulas; the interest of science lies in the art of making science.
    Paul Valéry (1871–1945)