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Title:On the Development of Inductive Learning Algorithms: Generating Flexible and Adaptable Concept Representations
Author(s):Vilalta, Ricardo
Doctoral Committee Chair(s):Larry Rendell
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Computer Science
Abstract:HCL achieves two functionalities: (1) flexibility in the representation, by increasing the complexity of the hypothesis comprised at each hierarchical layer, and (2) adaptability in the search for different representations, to know when to stop adding more layers in top of the hierarchical structure. Adaptability allows HCL to adjust the complexity of the representation by building few hierarchical levels when the concept is simple, and by increasing the number of levels as the difficulty of the concept grows higher. HCL is assessed experimentally using both artificial and real-world domains. Results show how HCL outperforms other models significantly when many intermediate concepts lie between the primitive features and the target concept. (Abstract shortened by UMI.).
Issue Date:1998
Description:178 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1998.
Other Identifier(s):(MiAaPQ)AAI9904611
Date Available in IDEALS:2015-09-25
Date Deposited:1998

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