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- W2037376884 abstract "A general decision analysis framework for identification of bacteria is made conspicuous. The classic identification models—binary decision tree and conditional probability models—are then enlightened in this framework and shown to be particular cases of multiattribute value function models. It is then suggested that the multicriteria collective choice rule approach can also be applied. This is illustrated by means of an experiment performed on the API commercial set of biochemical tests (identification of Enterobacteriaceae) with an ELECTRE-type model. It appears that the simultaneous use of conditional probability and ELECTRE models can improve the quality of identification. As they can be easily programmed on a microcomputer, these models are ipso facto a valuable aid to microbiologists." @default.
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- W2037376884 date "1984-01-01" @default.
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- W2037376884 title "Microcomputer-assisted identification of bacteria and multicriteria decision models" @default.
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- W2037376884 doi "https://doi.org/10.1016/0305-0548(84)90037-6" @default.
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