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1992 Volume 7
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RESEARCH ARTICLE   Open Access    

A unifying framework for concept-learning algorithms

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  • Abstract: A unifying framework for concept-learning, derived from Mitchell's Generalization as Search-paradigm, is presented. Central to the framework is the generic algorithm Gencol. Gencol forms a synthesis of existing concept-learning algorithms as it identifies the key issues in concept-learning: the representation of concepts and examples, the search strategy and heuristics, and the operators that transform one concept-description into another one when searching the concept description space. Gencol is relevant for practical purposes as it offers a solid basis for the design and implementation of concept-learning algorithms. The presented framework is quite general as seemingly disparate algorithms such as TDIDT, AQ, MIS and version spaces fit into Gencol.
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  • Cite this article

    Luc de Raedt, Maurice Bruynooghe. 1992. A unifying framework for concept-learning algorithms. The Knowledge Engineering Review. 7:6366 doi: 10.1017/S0269888900006366
    Luc de Raedt, Maurice Bruynooghe. 1992. A unifying framework for concept-learning algorithms. The Knowledge Engineering Review. 7:6366 doi: 10.1017/S0269888900006366
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RESEARCH ARTICLE   Open Access    

A unifying framework for concept-learning algorithms

  • Published online: 07 July 2009
The Knowledge Engineering Review  7,  Article number: 10.1017/S0269888900006366  (1992)  |  Cite this article

Abstract: Abstract: A unifying framework for concept-learning, derived from Mitchell's Generalization as Search-paradigm, is presented. Central to the framework is the generic algorithm Gencol. Gencol forms a synthesis of existing concept-learning algorithms as it identifies the key issues in concept-learning: the representation of concepts and examples, the search strategy and heuristics, and the operators that transform one concept-description into another one when searching the concept description space. Gencol is relevant for practical purposes as it offers a solid basis for the design and implementation of concept-learning algorithms. The presented framework is quite general as seemingly disparate algorithms such as TDIDT, AQ, MIS and version spaces fit into Gencol.

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    Luc de Raedt, Maurice Bruynooghe. 1992. A unifying framework for concept-learning algorithms. The Knowledge Engineering Review. 7:6366 doi: 10.1017/S0269888900006366
    Luc de Raedt, Maurice Bruynooghe. 1992. A unifying framework for concept-learning algorithms. The Knowledge Engineering Review. 7:6366 doi: 10.1017/S0269888900006366
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