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3. H. Ishibuchi, T. Nakashima, and T. Murata. Three-objective genetics-based machine learning for linguistic rule extraction. Information Sciences: An International Journal, 136:109-133, 2001. Keyword(s): pattern classification, fuzzy systems, genetic algorithm, rule extraction. [bibtex-entry]



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5. L. Chiang, E. Russell, and R. Braatz. Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis. Chemometrics and Intelligent Laboratory Systems, 50:243-252, 2000. Keyword(s): Fisher's discriminant analysis, discriminant partial least squares, principal component analysis, dimensionality reduction, multivariate statistics, large scale systems, fault detection, chemometric methods, discriminant analysis, pattern classification. [bibtex-entry]



6. M. Kbir, H. Benkirane, and R. Benslimane. Hierarchical fuzzy partition for pattern classification with fuzzy if-then rules. Pattern Recognition Letters, 21:503-509, 2000. Keyword(s): fuzzy classification problems, fuzzy if-then rules, hierarchical fuzzy partition. [bibtex-entry]



7. S. Martin, M. Kirby, and R. Miranda. Symmetric Veronese classifiers with application to materials design. Engineering Applications of Artificial Intelligence, 13:513-520, 2000. Keyword(s): feature selection, Veronese maps, materials design, pattern classification, support vector machines, kernel selection. [bibtex-entry]



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12. H. Ishibuchi, T. Murata, and I. Türksen. Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems. Fuzzy Sets and Systems, 89(2):135-150, 1997. Keyword(s): linguistic modeling, pattern recognition, data analysis, genetic algorithm, rule selection. [bibtex-entry]



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