A kind of non-classical logic requiring the antecedent and consequent of implications to be relevantly related, and aiming to capture aspects of implication that are ignored by the "material implication" operator in classical truth-functional logic.
In mathematics, a Relevance Vector Machine is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and probabilistic classification.