Multicriteria assignment method PROAFTN: Methodology and medical application

Belacel, Nabil

doi:10.1016/s0377-2217(99)00192-7

Cited by 147 publications

(118 citation statements)

References 8 publications

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“…This procedure solves a choice problem in order to determine a subset of k, k ≥ 1, nearest neighbors in terms of their resemblance, or similarity, with an object to be assigned. On the basis of the fuzzy scoring function [20][21] and the fuzzy indifference relations determined by the PROAFTN method [4][5][6][7][8], the PROCFTN procedure determines the k nearest neighbor prototypes. So, the PROCFTN method follows the k nearest neighbor (k-NN) procedure described by Cover and Hart [15].…”

Section: The Developed Methodsmentioning

confidence: 99%

“…As an example, we can cite medical diagnosis where the objects i.e., patients, presented by different symptoms and the prototypes are represented by typical symptoms [4][5][6][7][8].…”

Section: Multicriteria Classification Problemsmentioning

confidence: 99%

“…These advantages offered by the MCDA approach constitute the second reason for developing a procedure, which resorts to this approach. On the other hand only a few methods using MCDA approach have been applied in medical diagnosis [4][5][6][7][8]. This fact constitutes another reason for developing our method.…”

Section: Introductionmentioning

confidence: 99%

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Multicriteria fuzzy classification procedure PROCFTN: methodology and medical application

Belacel¹,

Boulassel

2004

Fuzzy Sets and Systems

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Abstract.In this paper we introduce a new classification procedure for assigning objects to predefined classes, named PROCFTN. 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, k-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.

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Section: The Developed Methodsmentioning

confidence: 99%

“…As an example, we can cite medical diagnosis where the objects i.e., patients, presented by different symptoms and the prototypes are represented by typical symptoms [4][5][6][7][8].…”

Section: Multicriteria Classification Problemsmentioning

confidence: 99%

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Multicriteria fuzzy classification procedure PROCFTN: methodology and medical application

Belacel¹,

Boulassel

2004

Fuzzy Sets and Systems

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“…The alternatives are defined on a number of 11 criteria which are valued on ratio scales in the interval [0,1]. This number has been chosen in order for the alternatives to resemble those from real problems that are considered to be difficult, but also allowing us to construct very diverse ones.…”

Section: Constructing the Benchmarksmentioning

confidence: 99%

“…In the case of the sorting problem, the profiles that are used to describe the classes already serve this purpose, however this is not the case for the other types of problems. We mention the central profiles [6,1] that are used for sorting into nominal classes, as well as the delimiting profiles [11,9] for sorting into ordered classes.…”

Section: Introductionmentioning

confidence: 99%

Descriptive Profiles for Sets of Alternatives in Multiple Criteria Decision Aid

Olteanu

Meyer

Bisdorff

2013

Algorithmic Decision Theory

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Abstract. In the context of Multiple Criteria Decision Aid, a decisionmaker may be faced at any time with the task of analysing one or several sets of alternatives, irrespective of the decision he is about to make. As in this case the alternatives may express contrasting gains and losses on the criteria on which they are evaluated, and while the sets that are presented to the decision-maker may potentially be large, the task of analysing them becomes a difficult one. Therefore the need to reduce these sets to a more concise representation is very important.Classically, profiles that describe sets of alternatives may be found in the context of the sorting problem, however they are either given beforehand by the decision-maker or determined from a set of assignment examples. We would therefore like to extend such profiles, as well as propose new ones, in order to characterise any set of alternatives. For each of them, we present several approaches for extracting them, which we then compare with respect to their performance.

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About the Application of Evidence Theory in Multicriteria Decision Aid

Boujelben

Smet

2013

Multicriteria Decision Aid and Artificial Intelligence

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Multicriteria assignment method PROAFTN: Methodology and medical application

Cited by 147 publications

References 8 publications

Multicriteria fuzzy classification procedure PROCFTN: methodology and medical application

Multicriteria fuzzy classification procedure PROCFTN: methodology and medical application

Descriptive Profiles for Sets of Alternatives in Multiple Criteria Decision Aid

About the Application of Evidence Theory in Multicriteria Decision Aid

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