Occam learning

In computational learning theory, Occam learning is a model of algorithmic learning where the objective of the learner is to output a succinct representation of received training data. ^[1]

4 relations: Computational learning theory, Concept class, Probably approximately correct learning, Structural risk minimization.

Computational learning theory

In computer science, computational learning theory (or just learning theory) is a subfield of Artificial Intelligence devoted to studying the design and analysis of machine learning algorithms.

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Concept class

A concept over a domain X is a total Boolean function over X. A concept class is a class of concepts.

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Probably approximately correct learning

In computational learning theory, probably approximately correct learning (PAC learning) is a framework for mathematical analysis of machine learning.

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Structural risk minimization

Structural risk minimization (SRM) is an inductive principle of use in machine learning.

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Occam Learning.

References

[1] https://en.wikipedia.org/wiki/Occam_learning

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