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- W1581532197 abstract "In this paper we present a way of constructing and using fuzzy decision trees for machine learning from sequential and incomplete data. We develop a theory and technique for processing such data. At first, we introduce a decision tree with fuzzy attributes and class the properties of fuzzy attributes and classes, where we will introduce the fuzzy division of objects in classes in a different way than that used in the literature. Then we will also introduce properties of fuzzy attribute value to enrich the fuzziness of our decision trees." @default.
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- W1581532197 date "2002-01-01" @default.
- W1581532197 modified "2023-10-14" @default.
- W1581532197 title "Learning Fuzzy Decision Trees from Sequential and Incomplete Data" @default.
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- W1581532197 doi "https://doi.org/10.1007/978-0-387-35602-0_24" @default.
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