Multicriteria fuzzy classification procedure PROCFTN: methodology and medical application

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DOIResolve DOI: https://doi.org/10.1016/S0165-0114(03)00022-8
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FormatText, Article
Journal titleFuzzy Sets and Systems
Volume14
Issues
Subjectmulticriteria decision aid; aide décisionnelle multicritères; classification; classification; Fuzzy sets; ensembles flous; Fuzzy binary relations; relations binaires floues; scoring function; fonction de score; astrocytic tumour; astrocytome; medical diagnosis; diagnostic médical
Abstract
In this paper we introduce a new classification procedure for assigning objects to predefined classes, named <em>PROCFTN</em>. This procedure is based on a fuzzy scoring function for choosing a subset of prototypes, which represent the closest resemblance with an object to be assigned. It then applies the majority-voting rule to assign an object to a class. We also present a medical application of this procedure as an aid to assist the diagnosis of central nervous system tumours. The results are compared with those obtained by other classification methods, reported on the same data set, including decision tree, production rules, neural network, <em>k</em>-nearest neighbour, multilayer perceptron and logistic regression. Our results are very encouraging and show that the multicriteria decision analysis approach can be successfully used to help medical diagnosis.
Publication date
PublisherElsevier
LanguageEnglish
Peer reviewedYes
NRC numberNRCC 44986
NPARC number8913214
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Record identifierb3dbebeb-f424-480d-8ec2-8a7b762bf795
Record created2009-04-22
Record modified2021-01-05
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