Integrating Inductive Learning to the Ripple Down Rules Method with the Minimum Description Length Principle

Author:

Wada Takuya1,Motoda Hiroshi1,Washio Takashi1

Affiliation:

1. The Institute of Scientific and Industrial Research, Osaka University.

Publisher

Japanese Society for Artificial Intelligence

Subject

Artificial Intelligence,Software

Reference17 articles.

1. [Blake 98] Blake, C. and Merz, C.: UCI Repository of machine learning databases (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html.

2. [Compton 89] Compton, P., Horn, K., Quinlan, J.R., and Lazarus, L.: Maintaining an Expert System, pp. 366-385, Addison Wesley (1989).

3. [Compton 95] Compton, P., Preston, P., and Kang, B.: The Use of Simulated Experts in Evaluating Knowledge Acquisition, in Proc. of the 9th Knowledge Acquisition for Knowledge Based Systems Workshop (1995).

4. [DEL 98] Data for Evaluating Learning Valid Experiments, The University of Toronto (1998), http://www.cs.utoronto.ca/~delve/data/datasets.html.

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1. Adaptive Ripple Down Rules Method based on Description Length;Transactions of the Japanese Society for Artificial Intelligence;2004

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