Abstract
A fuzzy data broswer for classification and prediction is described and its use demonstrated with several examples. The browser is written in the AI language Fril and provides a friendly user interface for the user to test the performance, see the effect of changes in the rules, visualise the performance and try various different forms of modelling. The rules with their associated fuzzy sets are automatically determined from a learning set of examples given in the form of a database. The fundamental theory of this approach to the automatic extraction of rules from data and the method of inference using these rules to generalise is described in simple terms. The method has wide application to data mining, fuzzy AI modelling, pattern recognition and computing with words.
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References
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© 1997 Springer-Verlag Berlin Heidelberg
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Baldwin, J.F., Martin, T.P. (1997). Basic concepts of a fuzzy logic data browser with applications. In: Nwana, H.S., Azarmi, N. (eds) Software Agents and Soft Computing Towards Enhancing Machine Intelligence. Lecture Notes in Computer Science, vol 1198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62560-7_47
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DOI: https://doi.org/10.1007/3-540-62560-7_47
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