Description

Here's the abstract from the above reference: ABSTRACT: Machine learning tools show significant promise for knowledge acquisition, particularly when human expertise is inadequate. Recently, process delays known as cylinder banding in rotogravure printing were substantially mitigated using control rules discovered by decision tree induction. Our work exemplifies a more general methodology which transforms the knowledge acquisition task from one in which rules are directly elicited from an expert, to one in which a learning system is responsible for rule generation. The primary responsibilities of the human expert are to evaluate the merits of generated rules, and to guide the acquisition and classification of data necessary for machine induction. These responsibilities require the expert to do what an expert does best: to exercise his or her expertise. This seems a more natural fit to an expert's capabilities than the requirements of traditional methodologies that experts explicitly enumerate the rules that they employ.

Related Papers

  • Juan J. Rodr##guez and Carlos J. Alonso and Henrik Bostrom. Learning First Order Logic Time Series Classifiers: Rules and Boosting. Grupo de Sistemas Inteligentes, Departamento de Inform#atica Universidad de Valladolid, Spain. [link]
  • Charles Campbell and Nello Cristianini. Simple Learning Algorithms for Training Support Vector Machines. Dept. of Engineering Mathematics. [link]
  • Juan J. Rodr##guez and Carlos J. Alonso and Henrik Bostrom. Boosting Interval Based Literals. 2000. [link]
  • Juan J Rodrguez Diez and Carlos Alonso Gonzlez and Henrik Bostrm. Learning First Order Logic Time Series Classifiers: Rules and Boosting. PKDD. 2000. [link]
  • Carlos J. Alonso Gonzalez and Juan J. Rodr and iguez Diez. Time Series Classification by Boosting Interval Based Literals. Grupo de Sistemas Inteligentes Departamento de Informatica Universidad de Valladolid. [link]
  • Juan J. Rodr##guez and Carlos J. Alonso. Applying Boosting to Similarity Literals for Time Series Classification. Department of Informatics University of Valladolid, Spain. 2000. [link]
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