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Hypothesis Language

  • Reference work entry
Encyclopedia of Machine Learning

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Synonyms

Representation language

Definition

The hypothesis language used by a machine learning system is the language in which the hypotheses (also referred to as patterns or models) it outputs are described.

Motivation and Background

Most machine learning algorithms can be seen as a procedure for deriving one or more hypotheses from a set of observations. Both the input (the observations) and the output (the hypotheses) need to be described in some particular language. This language is respectively called the Observation Language or the hypothesis language. These terms are mostly used in the context of symbolic learning, where these languages are often more complex than in subsymbolic or statistical learning. For instance, hypothesis languages have received a lot of attention in the field of Inductive Logic Programming, where systems typically take as one of their input parameters a declarative specification of the hypothesis language they are supposed to use (which is typically a...

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Recommended Reading

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Author information

Authors and Affiliations

    Authors
    1. Hendrik Blockeel
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    Editor information

    Editors and Affiliations

    1. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia, 2052

      Claude Sammut

    2. Faculty of Information Technology, Clayton School of Information Technology, Monash University, P.O. Box 63, Victoria, Australia, 3800

      Geoffrey I. Webb

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    © 2011 Springer Science+Business Media, LLC

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    Blockeel, H. (2011). Hypothesis Language. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_372

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