Synonyms
Definition
The hypothesis space used by a machine learning system is the set of all hypotheses that might possibly be returned by it. It is typically defined by a Hypothesis Language, possibly in conjunction with a Language Bias.
Motivation and Background
Many machine learning algorithms rely on some kind of search procedure: given a set of observations and a space of all possible hypotheses that might be considered (the “hypothesis space”), they look in this space for those hypotheses that best fit the data (or are optimal with respect to some other quality criterion).
To describe the context of a learning system in more detail, we introduce the following terminology. The key terms have separate entries in this encyclopedia, and we refer to those entries for more detailed definitions.
A learner takes observations as inputs. The Observation Language is the language used to describe these observations.
The hypotheses that a learner may produce, will be formulated in...
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Recommended Reading
De Raedt L (1992) Interactive theory revision: an inductive logic programming approach. Academic, London
Nédellec C, Adé H, Bergadano F, Tausend B (1996) Declarative bias in ILP. In: De Raedt L (ed) Advances in inductive logic programming. Frontiers in artificial intelligence and applications, vol 32. IOS Press, Amsterdam, pp 82–103
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Blockeel, H. (2017). Hypothesis Space. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_373
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_373
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Publisher Name: Springer, Boston, MA
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