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Differential Evolution for learning the classification method PROAFTN

โœ Scribed by Feras Al-Obeidat; Nabil Belacel; Juan A. Carretero; Prabhat Mahanti


Book ID
104035766
Publisher
Elsevier Science
Year
2010
Tongue
English
Weight
291 KB
Volume
23
Category
Article
ISSN
0950-7051

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The objectives of this paper are (1) to propose new techniques to learn and improve the multicriteria decision analysis (MCDA) method PROAFTN based on machine learning approaches and (2) to compare the performance of the developed methods with other well-known machine learning classification algorit