| Original language | English |
|---|---|
| Title of host publication | Encyclopedia of Machine Learning |
| Editors | Claude Sammut & Geoffrey I.Webb |
| Place of Publication | New York |
| Publisher | Springer |
| Pages | 5pp |
| Volume | 6 |
| ISBN (Print) | 9780387307688 |
| DOIs | |
| Publication status | Published - 2010 |
Abstract
Higher-order logic is a logic that admits so-called higher-order functions, which are functions that can have functions as arguments or return a function as a result. The expressive power that comes from higher-order functions makes the logic highly suitable for representing individuals, predicates, features, background theories, and hypotheses, and performing the necessary reasoning, in machine learning applications.
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