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- W839789112 abstract "The paper presents a general overview of recent methodology concerned with the problem of growing a decision tree in the presence of uncertainty or imprecision. One can identify two main approaches in the literature. The first aims at “softening” the hard recursive partition process through the use of fuzzy splits. The second proposes to handle the uncertainty by using more complex representation languages. Both approaches, which can be related in a probabilistic framework, produce in a general way more flexible and robust classification rules." @default.
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- W839789112 date "1998-01-01" @default.
- W839789112 modified "2023-09-24" @default.
- W839789112 title "Decision Trees and Uncertain Inference" @default.
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- W839789112 doi "https://doi.org/10.1007/978-3-642-72253-0_58" @default.
- W839789112 hasPublicationYear "1998" @default.
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