Matches in DBpedia 2016-04 for { ?s ?p "In computational learning theory, probably approximately correct learning (PAC learning) is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant.In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions."@en }
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- Probably_approximately_correct_learning comment "In computational learning theory, probably approximately correct learning (PAC learning) is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant.In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.".
- Q458526 comment "In computational learning theory, probably approximately correct learning (PAC learning) is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant.In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.".