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Kybernetika 36(6):689-705, 2000.

Fuzzy Decision Trees to Help Flexible Querying.

Christophe Marsala


Abstract:

Fuzzy data mining by means of the fuzzy decision tree method enables the construction of a set of fuzzy rules. Such a rule set can be associated with a database as a knowledge base that can be used to help answering frequent queries. In this paper, a study is done that enables us to show that classification by means of a fuzzy decision tree is equivalent to the generalized modus ponens. Moreover, it is shown that the decision taken by means of a fuzzy decision tree is more stable when observation evolves.


AMS: 04E;


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BIB TeX

@article{kyb:2000:6:689-705,

author = {Marsala, Christophe},

title = {Fuzzy Decision Trees to Help Flexible Querying.},

journal = {Kybernetika},

volume = {36},

year = {2000},

number = {6},

pages = {689-705}

publisher = {{\'U}TIA, AV {\v C}R, Prague },

}


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