Abstract
In this paper, a data mining process to induce a set of fuzzy rules from a database is presented. This process is based on the construction of fuzzy decision trees. We present a method to construct fuzzy decision trees and a method to use them to classify new examples. In presence of databases, prerequisites for training sets are introduced to generate a good subset of data that will enable us to construct a fuzzy decision tree. Moreover, we present different kinds of rules that can be induced by means of the construction of a decision tree, and we discuss some possible uses of such knowledge.
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Marsala, C. (1998). Application of fuzzy rule induction to data mining. In: Andreasen, T., Christiansen, H., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 1998. Lecture Notes in Computer Science, vol 1495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056007
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DOI: https://doi.org/10.1007/BFb0056007
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