article · 1994

Compositional Instance-Based Learning

Karl Branting, Patrick Broos

Cited by 0Abstract and details only

Abstract

This paper proposes a new algorithm for acquisition of preference predicates by a learning apprentice, termed Compositional Instance-Based Learning (CIBL), that permits multiple instances of a preference predicate to be composed, directly exploiting the transitivity of preference predicates. In an empirical evaluation, CIBL was consistently more accurate than a 1-NN instance-based learning strategy unable to compose instances. The relative performance of CIBL and decision tree induction was found to depend upon (1) the complexity of the preference predicate being acquired and (2) the dimensionality of the feature space.

Cite this paper

APA 7

Branting, K., & Broos, P. (1994). Compositional Instance-Based Learning.

MLA 9

Branting, Karl, and Patrick Broos. “Compositional Instance-Based Learning.” 1994.

Chicago

Branting, Karl, and Patrick Broos. 1994. “Compositional Instance-Based Learning.”

Harvard

Branting, K. and Broos, P. (1994) ‘Compositional Instance-Based Learning’.

BibTeX

@article{branting1994compositional,
  title = {{Compositional Instance-Based Learning}},
  author = {Branting, Karl and Broos, Patrick},
  year = {1994}
}

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