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MC-SC2 Publications about: classification
Books and proceedings
  1. A. Fielding. Cluster and Classification Techniques for the Biosciences. Cambridge University Press, Cambridge, 2006. [bibtex-entry]

  2. M. Doumpos and C. Zopounidis. Multicriteria Decision Aid Classification Methods, volume 73 of Applied Optimization. Springer, Formerly Kluwer Academic Publishers, Boston, Dordrecht, London, 2002. [bibtex-entry]

  3. K. Jajuga, A. Sokolowski, and H.-H. Bock, editors. Classification, Clustering and Data Analysis: Recent Advances and Applications, Studies in Classification, Data Analysis & Knowledge Organization. Springer-Verlag, Berlin, 2002. [bibtex-entry]

  4. A. Rizzi, M. Vichi, and H.-H. Bock, editors. Advances in Data Science and Classification, Studies in Classification, Data Analysis & Knowledge Organization. Springer-Verlag, Berlin, 1998. [bibtex-entry]

  1. L. Henriet. Systèmes d'évaluation et de classification multicritères pour l'aide à la décision. Construction de modèles et procédures d'affectation. Thése de Doctorat, Université Paris Dauphine, Paris, France, 2000. [bibtex-entry]

  2. N. Belacel. Méthodes de Classification Multicritère : Méthodologie et Application au Diagnostique Médical. Thése deDoctorat, Université Libre de Bruxelles, Belgique, 1998. Keyword(s): PROAFTN. [bibtex-entry]

Articles in journal or book chapters
  1. N. Belacel, H. Raval, and A. Punnen. Learning multicriteria fuzzy classification method PROAFTN from data. Computers & Operations Research, 34(7):1885-1898, 2007. Keyword(s): data mining, multiple criteria classification, PROAFTN, variable neighborhood search. [bibtex-entry]

  2. J. Blaszczynski, S. Greco, and R. Słowiński. Multi-criteria classification: A new scheme for application of dominance-based decision rules. European Journal of Operational Research, 2006. Note: In Press. Keyword(s): multi-criteria classification, rough sets, dominance, decision rules, classifiers. [bibtex-entry]

  3. Y. Chen, D. Kilgour, and K. Hipel. Multiple criteria classification with an application in water resources planning. Computers & Operations Research, 33(11):3301-3323, 2006. Keyword(s): multiple criteria decision aid, sorting, nominal classification, resource management. [bibtex-entry]

  4. C. Cifarelli, L. Nieddu, O. Seref, and P. Pardalos. K-T.R.A.C.E: A kernel k-means procedure for classification. Computers & Operations Research, 2006. Note: In Press. Keyword(s): classification, k-means, kernel functions. [bibtex-entry]

  5. V. Hontou, D. Diakoulaki, and L. Papagiannakis. A multicriterion classification approach for assessing the impact of environmental policies on the competitiveness of firms. Corporate Social Responsibility and Environmental Management, 2006. Note: In Press. [bibtex-entry]

  6. K. Kosmidou, F. Pasiouras, C. Zopounidis, and M. Doumpos. A multivariate analysis of the financial characteristics of foreign and domestic banks in the UK. Omega - The International Journal of Management Science, 34(2):189-195, 2006. Keyword(s): bank performance, logistic regression, classification. [bibtex-entry]

  7. H. Lee, H. Chen, and J. Lin. K-means method for rough classification of R&D employees' performance evaluation. International Transactions in Operational Research, 13(4):365-377, 2006. [bibtex-entry]

  8. F. Pasiouras, Ch. Gaganis, and C. Zopounidis. Multicriteria decision support methodologies for auditing decisions: The case of qualified audit reports in the UK. European Journal of Operational Research, 2006. Note: In Press. Keyword(s): multicriteria analysis, auditing, classification, case study. [bibtex-entry]

  9. F. Pasiouras, S. Tanna, and C. Zopounidis. The identification of acquisition targets in the EU banking industry: An application of multicriteria approaches. International Review of Financial Analysis, 2006. Note: In Press. Keyword(s): acquisitions, banks, classification, MCDA. [bibtex-entry]

  10. Z.-X. Sun, M. Han, and W.-H. Qiu. Classification approach for multicriteria decision making problem. Kongzhi yu Juece/Control and Decision, 21(2):171-174, 2006. Keyword(s): classification, linear programming, multicriteria decision making, valued outranking relation. [bibtex-entry]

  11. T. Van Gestel, B. Baesens, J. Suykens, D. Van den Poel, D.-E. Baestaens, and M. Willekens. Bayesian kernel based classification for financial distress detection. European Journal of Operational Research, 172(3):979-1003, 2006. Note: VanGestelETAL05. Keyword(s): credit scoring, kernel Fisher discriminant analysis, least squares support vector machine classifiers, bayesian inference. [bibtex-entry]

  12. J. Wang. Multi-criteria classification approach with polynomial aggregation function and incomplete certain information. Journal of Systems Engineering and Electronics, 17(3):546-550, 2006. Keyword(s): multi-criteria, decision-making, incomplete certain information, polynomial function, classification. [bibtex-entry]

  13. I. Yevseyeva, K. Miettinen, and P. Räsänen. Verbal ordinal classification with multicriteria decision aiding. European Journal of Operational Research, 2006. Note: In Press. Keyword(s): multiple criteria analysis, decision support systems, verbal decision analysis, dichotomic, classification, neuropsychological diagnostics. [bibtex-entry]

  14. P. Zhou and L. Fan. A note on multi-criteria ABC inventory classification using weighted linear optimization. European Journal of Operational Research, 2006. Note: In Press. Keyword(s): inventory, multiple criteria analysis, classification. [bibtex-entry]

  15. M. Beynon. A novel technique of object ranking and classification under ignorance: An application to the corporate failure risk problem. European Journal of Operational Research, 167:493-517, 2005. [bibtex-entry]

  16. J. Dombi and A. Zsiros. Learning multicriteria classification models from examples: Decision rules in continuous space. European Journal of Operational Research, 160(3):663-675, 2005. Keyword(s): multiple criteria analysis, classification, artificial intelligence, decision trees, fuzzy sets. [bibtex-entry]

  17. M. Doumpos and F. Pasiouras. Developing and testing models for replicating credit ratings: A multicriteria approach. Computational Economics, 25:327-341, 2005. Keyword(s): credit rating, classification, model testing, multicriteria decision aid. [bibtex-entry]

  18. H. Essaqote, N.-E. Zahid, M. Limouri, and A. Essaid. A new approach for unsupervised classification. 4OR: A Quarterly Journal of Operations Research, 3(1):39-49, 2005. Keyword(s): unsupervised classification, unidimensional histograms, concave segment, mode detection. [bibtex-entry]

  19. Ch. Gaganis, F. Pasiouras, and A. Tzanetoulakos. A comparison and integration of classification techniques for the prediction of small UK firms failure. The Journal of Financial Decision Making, 1(1):61-75, 2005. [bibtex-entry]

  20. B. Mohanty and B. Bhasker. Product classification in the Internet business: A fuzzy approach. Decision Support Systems, 38(4):611-619, 2005. Keyword(s): Internet, fuzzy sets, linguistic quantifier, hierarchical level, product attributes, product classification. [bibtex-entry]

  21. A. Salappa, M. Doumpos, and C. Zopounidis. Feature selection algorithms in classification problems: An experimental evaluation. Foundations of Computing and Decision Sciences, 30(4):331-349, 2005. Keyword(s): feature selecion, pattern recognition, decision analysis, performance evaluation. [bibtex-entry]

  22. N. Belacel. The k-closest resemblance approach for multiple criteria classification problems. In L.-T. Hoai and P. Tao, editors, Modelling, Computation and Optimization Information and Management Sciences, pages 525-534. Hermes Sciences Publishing, 2004. [bibtex-entry]

  23. A. Amo, J. Montero, G. Biging, and V. Cutello. Fuzzy classification systems. European Journal of Operational Research, 156(2):495-507, 2004. Keyword(s): classification, fuzzy sets, fuzzy partition, multicriteria analysis. [bibtex-entry]

  24. J.-P. Barthélemy, F. Brucker, and C. Osswald. Combinatorial optimization and hierarchical classifications. 4OR: A Quarterly Journal of Operations Research, 2(3):179-219, 2004. Keyword(s): hierarchical classification, quasi-hierarchies, rigid hypergraphs, complexity, clustering algorithms, subdominant. [bibtex-entry]

  25. N. Belacel and M. Boulassel. Multicriteria fuzzy classification procedure PROCFTN: Methodology and medical application. Fuzzy Sets and Systems, 141(2):203-217, 2004. Keyword(s): multicriteria decision aid, classification, fuzzy sets, fuzzy binary relations, scoring function, astrocytic tumour, medical diagnosis, PROCFTN. [bibtex-entry]

  26. M. Doumpos and C. Zopounidis. A multicriteria classification approach based on pairwise comparisons. European Journal of Operational Research, 158(2):378-389, 2004. Keyword(s): multicriteria analysis, classification, preference relation, linear programming. [bibtex-entry]

  27. R. Ramanathan. ABC inventory classification with multiple-criteria using weighted linear optimization. Computers & Operations Research, 2004. Keyword(s): ABC inventory classification, multiple criteria, weighted linear optimization. [bibtex-entry]

  28. H. Schneiderman and T. Kanade. Object Detection Using the Statistics of Parts. International Journal of Computer Vision, 56(3):151-177, 2004. Keyword(s): object recognition, object detection, face detection, car detection, pattern recognition, machine learning, statistics, computer vision, wavelets, classification. [bibtex-entry]

  29. S. Sohn and C. Dagli. Ensemble of Evolving Neural Networks in Classification. Neural Processing Letters, 19(3):191-203, 2004. Keyword(s): classification, combining classifiers, data mining, genetic algorithm, neural networks. [bibtex-entry]

  30. C. Zopounidis, M. Doumpos, and P. Pardalos. Computational Classification Methods for Decision Making. Computational Management Science, 1(3-4):209-343, 2004. [bibtex-entry]

  31. J. Abonyi, J. Roubos, and F. Szeifert. Data-driven generation of compact, accurate, and linguistically sound fuzzy classifiers based on a decision-tree initialization. International Journal of Approximate Reasoning, 32(1):1-21, 2003. Keyword(s): classification, fuzzy classifier, decision tree, genetic algorithm, model reduction. [bibtex-entry]

  32. V. Ananthanarayana, M. Murty, and D. Subramanian. Tree structure for efficient data mining using rough sets. Pattern Recognition Letters, 24(6):851-862, 2003. Note: Short Communication. Keyword(s): PC-tree, single database scan, dynamic mining, segment PC-tree, rough PC-tree, classification, rough sets. [bibtex-entry]

  33. S. Bose. Multilayer statistical classifiers. Computational Statistics & Data Analysis, 42(4):685-701, 2003. Keyword(s): classification, cubic splines, discriminant analysis, neural networks, CART, simulation. [bibtex-entry]

  34. L. C. Dias and V. Mousseau. IRIS: A DSS for multiple criteria sorting problems. Journal of Multi-Criteria Decision Analysis, 12(4-5):285 - 298, 2003. Keyword(s): decision support systems, sorting, classification, ELECTRE TRI, software. [bibtex-entry]

  35. J. Glen. An iterative mixed integer programming method for classification accuracy maximizing discriminant analysis. Computers & Operations Research, 30:181-198, 2003. Keyword(s): discriminant analysis, mathematical programming, variable selection. [bibtex-entry]

  36. Y.-C. Hu, R.-S. Chen, and G.-H. Tzeng. Finding fuzzy classification rules using data mining techniques. Pattern Recognition Letters, 24:509-519, 2003. Keyword(s): data mining, fuzzy sets, classification, genetic algorithm. [bibtex-entry]

  37. M. Hüsken and P. Stagge. Recurrent neural networks for time series classification. Neurocomputing, 50:223-235, 2003. Keyword(s): recurrent neural network, classification, time series, multitask learning, generalization. [bibtex-entry]

  38. T. Khoshgoftaar, Y. Liu, and N. Seliya. Genetic programming-based decision trees for software quality classification. IEEE - The Institute of Electrical and Electronics Engineers, pp 374-383, 2003. Keyword(s): software metrics, genetic programming, decision tree, software quality classification, multiobjective optimization, cost of misclassification. [bibtex-entry]

  39. K. Lam and J. Moy. A simple weighting scheme for classification in two-group discriminant problems. Computers & Operations Research, 30:155-164, 2003. Keyword(s): classification, discriminant analysis, linear programming, statistics. [bibtex-entry]

  40. Y. Lu and J. Han. Cancer classification using gene expression data. Information Systems, 28(4):243-268, 2003. Keyword(s): cancer classification, gene expression data. [bibtex-entry]

  41. S. Pang, D. Kim, and S. Bang. Membership authentication in the dynamic group by face classification using SVM ensemble. Pattern Recognition Letters, 24:215-225, 2003. Keyword(s): membership authentication, Gabor filter, principal component analysis, linear discriminant analysis, support vector machine ensemble. [bibtex-entry]

  42. C. Priebe, D. Marchette, J. DeVinney, and D. Socolinsky. Classification using class cover catch digraphs. Journal of Classification, 20:3-23, 2003. Keyword(s): classification, random graph, class cover, prototype selection. [bibtex-entry]

  43. J. Roubos, M. Setnes, and J. Abonyi. Learning fuzzy classification rules from labeled data. Information Sciences: An International Journal, 150(1-2):77-93, 2003. Keyword(s): compact fuzzy classifier, linguistic model, genetic algorithm, similarity-driven rule-base reduction, wine data. [bibtex-entry]

  44. I. Tabus, J. Rissanen, and J. Astola. Classification and feature gene selection using the normalized maximum likelihood model for discrete regression. Signal Processing, 83(4):713-727, 2003. Keyword(s): classification, feature selection, gene expression, discrete regression, minimum description length, normalized maximum likelihood. [bibtex-entry]

  45. A. Vieira and N. Barradas. A training algorithm for classification of high-dimensional data. Neurocomputing, 50:461-472, 2003. Keyword(s): classification, learning vector quantization, hidden layer learning vector quantization, feature extraction, rutherford backscattering. [bibtex-entry]

  46. M. Doumpos and C. Zopounidis. On the use of multicriteria classification methods: A simulation study. In D. Bouyssou, E. Jacquet-Lagrèze, P. Perny, R. Słowiński, D. Vanderpooten, and Ph. Vincke, editors, Aiding Decisions with Multiple Criteria: Essays in Honour of Bernard Roy, volume 44 of International Series in Operations Research and Management Science, pages 211-228. Springer, Formerly Kluwer Academic Publishers, Boston, Dordrecht, London, 2002. Keyword(s): classification, multicriteria decision aid, Monte Carlo simulation, multivariate statistical analysis, UTADIS. [bibtex-entry]

  47. A. Bröder. Take The Best, Dawes' Rule, and Compensatory Decision Strategies: A Regression-based Classification Method. Quality & Quantity, 36:219-238, 2002. Keyword(s): decision making, take the best, probabilistic inference, hypothesis testing, strategy classification. [bibtex-entry]

  48. V. Bugera, H. Konno, and S. Uryasev. Credit cards scoring with quadratic utility functions. Journal of Multi-Criteria Decision Analysis, 11(4-5):197-211, 2002. Keyword(s): credit cards scoring, utility functions, linear programming, classification. [bibtex-entry]

  49. B.-C. Chien, J. Lin, and T.-P. Hong. Learning discriminant functions with fuzzy attributes for classification using genetic programming. Expert Systems with Applications: An International Journal, 23:31-37, 2002. Keyword(s): classification, genetic programming, knowledge discovery, fuzzy sets. [bibtex-entry]

  50. J. DeVinney and J. Wierman. A SLLN for a one-dimensional class cover problem. Statistics & Probability Letters, 59:425-435, 2002. Keyword(s): class cover problem, catch disgraphs, domination, poisson process, complete convergence, strong law of large numbers, classification, pattern recognition. [bibtex-entry]

  51. K. Dembczynski, S. Greco, and R. Słowiński. Methodology of rough-set-based classification and sorting with hierarchical structure of attributes and criteria. Control & Cybernetics, 31:891-920, 2002. [bibtex-entry]

  52. M. Doumpos, K. Kosmidou, G. Baourakis, and C. Zopounidis. Credit risk assessment using a multicriteria hierarchical discrimination approach: A comparative analysis. European Journal of Operational Research, 138(2):392-412, 2002. Keyword(s): credit risk assessment, multicriteria decision aid, classification, case study, M.H.DIS. [bibtex-entry]

  53. M. Doumpos and C. Zopounidis. Business failure prediction: A comparison of classification methods. Operations Research: An International Journal, 2(3), 2002. [bibtex-entry]

  54. M. Doumpos and C. Zopounidis. Multi–criteria classification methods in financial and banking decisions. International Transactions in Operational Research, 9(5):567-581, 2002. [bibtex-entry]

  55. M. Doumpos and C. Zopounidis. On the development of an outranking relation for ordinal classification problems: An experimental investigation of a new methodology. Optimization Methods and Software, 17(2):293-317, 2002. Keyword(s): classification, multicriteria decision aid, linear programming, Monte Carlo simulation. [bibtex-entry]

  56. M. Doumpos and C. Zopounidis. On the use of a multi-criteria hierarchical discrimination approach for country risk assessment. Journal of Multi-Criteria Decision Analysis, 11(4-5):279-289, 2002. Keyword(s): country risk assessment, classification, preference disaggregation, comparison. [bibtex-entry]

  57. M. Doumpos and C. Zopounidis. Rough sets and multivariate statistical classification: A simulation study. Computational Economics, 19(3):287-301, 2002. Keyword(s): classification, rough sets theory, multivariate statistics, Monte Carlo simulation. [bibtex-entry]

  58. C. Ellwein, S. Danaher, and U. Jäger. Identifying regions of interest in spectra for classification purposes. Mechanical Systems and Signal Processing, 16(2-3):211-222, 2002. [bibtex-entry]

  59. S. Greco, B. Matarazzo, and R. Słowiński. Rough sets methodology for sorting problems in presence of multiple attributes and criteria. European Journal of Operational Research, 138(2):247-259, 2002. Keyword(s): rough sets, sorting, classification, multiple criteria decision analysis, decision rules. [bibtex-entry]

  60. K. Ha, J. Jo, S.-W. Kim, and J.-B. Lee. Classification of free actions of finite groups on the 3-torus. Topology and its Applications, 121:469-507, 2002. Keyword(s): group actions, bieberbach groups, affine conjugacy. [bibtex-entry]

  61. Y.-C. Hu, R.-S. Chen, and G.-H. Tzeng. Mining fuzzy association rules for classification problems. Computers & Industrial Engineering, 43:735-750, 2002. Keyword(s): data mining, knowledge acquisition, classification, association rules. [bibtex-entry]

  62. K. Lam and J. Moy. Combining discriminant methods in solving classification problems int two-group discriminant analysis. European Journal of Operational Research, 138:294-301, 2002. Keyword(s): linear programming, goal programming, multivariate statistics, classification, combining, discriminant analysis. [bibtex-entry]

  63. O. Larichev, A. Asanov, and Y. Naryzhny. Effectiveness evaluation of expert classification methods. European Journal of Operational Research, 138(2):260-273, 2002. Keyword(s): multiple criteria analysis, multicriteria classification, expert knowledge, complete and non-contradictory knowledge base, monotone function decoding, algorithm optimal by Shannon. [bibtex-entry]

  64. O. Larichev, A. Kortnev, and D. Kochin. Decision support system for classification of a finite set of multicriteria alternatives. Decision Support Systems, 33(1):13-21, 2002. Keyword(s): decision maker, decision support systems, multicriteria classification problems, ORCLASS. [bibtex-entry]

  65. J. Léger and J.-M. Martel. A multicriteria assignment procedure for a nominal sorting problematic. European Journal of Operational Research, 138(2):349-364, 2002. Keyword(s): multicriteria method, nominal sorting problematic, classification, assignment, similarity. [bibtex-entry]

  66. R. Pavur. A comparative study of the effect of the position of outliers on classical and nontraditional approaches to the two-group classification probelm. European Journal of Operational Research, 136:603-615, 2002. Keyword(s): Monte Carlo simulation, classification, mathematical programming, multivariate statistics. [bibtex-entry]

  67. P. Pendharkar. A potencial use of data envelopment analysis for the inverse classification problem. Omega - The International Journal of Management Science, 30:243-248, 2002. Keyword(s): classification, data envelopment analysis, linear programming, discriminant analysis. [bibtex-entry]

  68. M. Sarkar. Rough-fuzzy functions in classification. Fuzzy Sets and Systems, 132:353-369, 2002. Keyword(s): fuzzy sets, rough sets, rough-fuzzy sets, membership functions, classification, entropy. [bibtex-entry]

  69. Y. Shan, R. Zhao, G. Xu, H. Liebich, and Y. Zhang. Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data. Analytica Chimica Acta, 471:77-86, 2002. Keyword(s): classification, cancer, nucleosides, probabilistic neural network. [bibtex-entry]

  70. Q. Shen and A. Chouchoulas. A rough-fuzzy approach for generating classification rules. Pattern Recognition, 35:2425-2438, 2002. Keyword(s): pattern classification, rough sets, fuzzy sets, feature selection, rule induction. [bibtex-entry]

  71. M. Sun. A multiple objective programming approach for determining faculty salary equity adjustments. European Journal of Operational Research, 138(2):302-319, 2002. Keyword(s): multiple objective programming, multiple criteria decision making, classification, faculty salary, compensation. [bibtex-entry]

  72. N. Ye and X. Li. A scalable, incremental learning algorithm for classification problems. Computers & Industrial Engineering, 43:677-692, 2002. Keyword(s): data mining, classification, incremental learning, scalability. [bibtex-entry]

  73. C. Zopounidis and M. Doumpos. Multicriteria classification and sorting methods: A literature review. European Journal of Operational Research, 138(2):229-246, 2002. Keyword(s): multiple criteria analysis, classification, sorting, utility functions, outranking relations, decision rules, preference disaggregation. [bibtex-entry]

  74. A. Agarwal, J. Davis, and T. Ward. Supporting ordinal four-state classification decisions using neural networks. Information Technology and Management, 2(1):5-26, 2001. Keyword(s): decision support systems, neural networks, ordinal multi-state classification, financial distress. [bibtex-entry]

  75. N. Belacel and M. Boulassel. Multicriteria fuzzy assignment method: A useful tool to assist medical diagnosis. Artificial Intelligence in Medicine, 21, 2001. Keyword(s): multicriteria decision aid, classification, fuzzy sets, medical applications. [bibtex-entry]

  76. N. Belacel and M. Boulassel. Multicriteria fuzzy assignment method: A useful tool to assist medical diagnosis. Artificial Intelligence in Medicine, 21:201-207, 2001. Keyword(s): multicriteria decision aid, classification, fuzzy sets, PROAFTN. [bibtex-entry]

  77. N. Belacel, Ph. Vincke, M. Scheiff, and M. Boulassel. Acute leukemia diagnosis aid software using multicriteria fuzzy assignment methodology. Computer Methods and Programs in Biomedicine, 64(2):145-151, 2001. Keyword(s): computer-aided diagnosis, classification, fuzzy sets, fuzzy relations, acute leukemia. [bibtex-entry]

  78. R. De and S. Pal. A connectionist model for selection of cases. Information Sciences: An International Journal, 132:179-194, 2001. Keyword(s): case-based reasoning, fuzzy similarity, classification, node growing, node puning. [bibtex-entry]

  79. L. Di Lascio, A. Gisolfi, and G. Rosa. A commutative l-monoid for classification with fussy attributes. International Journal of Approximate Reasoning, 26:1-46, 2001. Keyword(s): fuzzy number, monoid, lattice, classical partition, relevance, classification. [bibtex-entry]

  80. M. Doumpos, S. Zanakis, and C. Zopounidis. Multicriteria preference disaggregation for classification problems with an application to global investing risk. Decision Sciences, 32(2):333-385, 2001. Keyword(s): financial DSS, globalization, investment risk, judgment analysis, mathematical programming, multicriteria decision making, regression, classification, discriminant analysis. [bibtex-entry]

  81. M. Doumpos and C. Zopounidis. Assessing financial risks using a multicriteria sorting procedure: The case of country risk assessment. Omega - The International Journal of Management Science, 29(1):97-109, 2001. Keyword(s): classification, country risk, discriminant analysis, multicriteria. [bibtex-entry]

  82. M. Doumpos and C. Zopounidis. On the use of multicriteria classification methods: A simulation study. Fuzzy Economic Review, 6(2):37-49, 2001. [bibtex-entry]

  83. S. Greco, B. Matarazzo, and R. Słowiński. Rough sets theory for multicriteria decision analysis. European Journal of Operational Research, 129(1):1-47, 2001. Keyword(s): multicriteria decision analysis, rough sets, classification, sorting, choice, ranking, decision rules, conjoint measurement. [bibtex-entry]

  84. A. Gómez-Skarmeta, M. Valdés, F. Jiménez, and J. Marìn-Blásquez. Approximative fuzzy rules approaches for classification with hybrid-GA techniques. Information Sciences: An International Journal, 136:193-214, 2001. Keyword(s): fuzzy classifiers, hybrid systems, rules extraction, fuzzy rules tuning, fuzzy hedges. [bibtex-entry]

  85. J. Kishore, L. Patnaik, V. Mani, and V. Agrawal. Genetic programming based pattern classification with feature space partitioning. Information Sciences: An International Journal, 131:65-86, 2001. [bibtex-entry]

  86. C. Loucopoulos. Three-group classification with unequal misclassification costs: A mathematical programming approach. Omega - The International Journal of Management Science, 29:291-297, 2001. Keyword(s): mathematical programming, discriminant analysis, MBA admissions. [bibtex-entry]

  87. M. Pardo, G. Sberveglieri, A. Taroni, F. Masulli, and G. Valentini. Decompositive classification models for Electronic Noses. Analytica Chimica Acta, 446:223-232, 2001. Keyword(s): pattern recognition, ensemble methods, classification tree, output coding, multilayer perception, electronic nose. [bibtex-entry]

  88. P. Pendharkar. An empirical study of design and testing of hybrid evolutionary-neural approach for classification. Omega - The International Journal of Management Science, 29:361-374, 2001. Keyword(s): artificial intelligence, artificial neural networks, genetic algorithm, discriminant analysis, classification, learning. [bibtex-entry]

  89. V. Ravi, P. Reddy, and H.-J. Zimmermann. Fuzzy rule base generation for classification and its minimization via modified threshold accepting. Fuzzy Sets and Systems, 120(2):271-279, 2001. Keyword(s): fuzzy if-then rule bases, modifed threshold accepting, meta-heuristics, multi objective combinatorial optimization problem. [bibtex-entry]

  90. C. Zopounidis and M. Doumpos. A preference disaggregation decision support system for financial classification problems. European Journal of Operational Research, 130(2):402-413, 2001. Keyword(s): multicriteria analysis, decision support systems, finance, preference disaggregation, credit granting. [bibtex-entry]

  91. N. Belacel. Multicriteria assignment method PROAFTN: Methodology and medical application. European Journal of Operational Research, 125(1):175-183, 2000. Keyword(s): multicriteria decision analysis, classification, fuzzy assignment, medical diagnosis. [bibtex-entry]

  92. J. Dona, J. Peláez, A. Holgado, and O. Hidalgo. Analysis of the genetic algorithm Gamic for multicriteria classification of inventories. IEEE - The Institute of Electrical and Electronics Engineers, 2:606-611, 2000. Keyword(s): genetic algorithm, AHP, inventory, rank reversal, multi-criteria analysis. [bibtex-entry]

  93. O. Ekin, P. Hammer, and A. Kogan. Convexity and logical analysis of data. Theoretical Computer Science, 244(1-2):95-116, 2000. Keyword(s): partially-defined boolean functions, orthogonal disjunctive normal forms, computational learning theory, classification, polynomial algorithms. [bibtex-entry]

  94. 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]

  95. S. Lee. Noisy replication in skewed binary classification. Computational Statistics & Data Analysis, 34:165-191, 2000. Keyword(s): ROC curve, Kullback-Leibler distance. [bibtex-entry]

  96. R. Major and C. Ragsdale. An aggregation approach to the classification problem using multiple prediction experts. Information Processing and Management, 36:683-696, 2000. Keyword(s): discriminant analysis, aggregation, binary classification, maximum entropy, binomial weights. [bibtex-entry]

  97. M. Mannino and M. Koushik. The cost-minimizing inverse classification problem: A genetic algorithm approach. Decision Support Systems, 29:283-300, 2000. Keyword(s): inverse classification, genetic algorithm, classification systems, sensitivity analysis. [bibtex-entry]

  98. W. Nettleton, C. Olson, and D. Wysocki. Paleosol classification: Problem and solutions. Catena, 41:61-92, 2000. Keyword(s): paleosol, paleoenvironment, property-based classification system. [bibtex-entry]

  99. M. Pardo, G. Sberveglieri, S. Gardini, and E. Dalcanale. A hierarchical classification scheme for an Electronic Nose. Sensors and Actuators B: Chemical, 69:359-365, 2000. Keyword(s): hierarchical classification, pattern recognition, ANN, Simca, electronic nose. [bibtex-entry]

  100. R. Paredes and E. Vidal. A class-dependent weighted dissimilarity measure for nearest neighbor classification problems. Pattern Recognition Letters, 21:1027-1036, 2000. Keyword(s): nearest neighbor classification, weighted dissimilarity measures, iterative optimization, fractional programming. [bibtex-entry]

  101. V. Ravi, P. Reddy, and H.-J. Zimmermann. Pattern classification with principal component analysis and fuzzy rule bases. European Journal of Operational Research, 126:526-533, 2000. Keyword(s): fuzzy sets, data analysis, feature selection, principal component analysis, modified threshold accepting. [bibtex-entry]

  102. V. Ravi and H.-J. Zimmermann. Fuzzy rule based classification with FeatureSelector and modified threshold accepting. European Journal of Operational Research, 123(1):16-28, 2000. Keyword(s): fuzzy sets, feature selection, fuzzy if-then rule bases, modified threshold accepting, meta-heuristics, multiobjective combinatorial optimization problem. [bibtex-entry]

  103. R. Sexton and R. Dorsey. Reliable classification using networks: A genetic algorithm and backpropagation comparison. Decision Support Systems, 30:11-22, 2000. Keyword(s): neural networks, genetic algorithm, backpropagation, decision support systems, classification, artificial intelligence. [bibtex-entry]

  104. J. Shen, W. Shen, H. Sun, and J. Yang. Fuzzy neural nets with non-summetric p membership functions and applications in signal processing and image analysis. Signal Processing, 80:965-983, 2000. Keyword(s): fuzzy neural network, learning, non-symmetric pi membership function, interpolation, approximation, estimation, classification, texture. [bibtex-entry]

  105. A. Valls and V. Torra. Using classification as an aggregation tool in MCDM. Fuzzy Sets and Systems, 115(1):159-168, 2000. Keyword(s): decision making, multicriteria analysis, cluster analysis, aggregation operators. [bibtex-entry]

  106. R. Östermark. A hybrid genetic fuzzy neural network algorithm designed for classification problems involving several groups. Fuzzy Sets and Systems, 114:311-324, 2000. Keyword(s): hybrid fuzzy neural networks, fuzzy sets, evolutionary computation, multigroup classification. [bibtex-entry]

  107. N. Bolloju. Decision model formulation of subjective classification problem-solving knowledge using a neuro-fuzzy classifier and its effectiveness. International Journal of Approximate Reasoning, 21:197-213, 1999. Keyword(s): model formulation, fuzzy logic, knowledge discovery, decision modeling, neuro-fuzzy systems, classifications problems. [bibtex-entry]

  108. J.-Y. Cai. A classification of the probabilistic polynomial time hierarchy under fault tolerant access to oracle classes. Information Processing Letters, 69:167-174, 1999. Keyword(s): computational complexity, fault tolerance, theory of computation. [bibtex-entry]

  109. A. Dimitras, R. Słowiński, R. Susmaga, and C. Zopounidis. Business failure prediction using rough sets. European Journal of Operational Research, 114(2):263-280, 1999. Keyword(s): business failure prediction, rough set theory, discriminant analysis, decision rules, classification. [bibtex-entry]

  110. C. Emmanouilidis, A. Hunter, J. MacIntyre, and C. Cox. Multiple-criteria genetic algorithms for feature selection in neuro-fuzzy modeling. IEEE Transactions on Neural Networks, 6:4387-4392, 1999. Keyword(s): multiobjective genetic algorithms, fuzzy models, classification, feature selection, data mining. [bibtex-entry]

  111. R. Glendinning. Robust shape classification. Signal Processing, 77:121-138, 1999. Keyword(s): shape classification, sub-set autoregression, additive outliers, robust identification, lag selection, fault detection. [bibtex-entry]

  112. H. Ishibuchi, T. Nakashima, and T. Morisawa. Voting in fuzzy rule-based systems for pattern classification problems. Fuzzy Sets and Systems, 103:223-238, 1999. Keyword(s): pattern classification, fuzzy rule-based systems, fuzzy reasoning, voting schemes. [bibtex-entry]

  113. I. Jagielska, C. Matthews, and T. Whitfort. An investigation into the application of neural networks, fuzzy logic, genetic algorithms, and rough sets to automated knowledge acquisition for classification problems. Neurocomputing, 24:37-54, 1999. Keyword(s): automated knowledge acquisition, fuzzy rule extraction, fuzzy classification systems, neural networks, genetic algorithm, rough sets. [bibtex-entry]

  114. M. Lortie and P. Rizzo. The classification of accident data. Safety Science, 31:31-57, 1999. Keyword(s): accident, first accident report, classification, incident, activity. [bibtex-entry]

  115. P. Mangiameli and D. West. An improved neural classification network for the two-group problem. Computers & Operations Research, 26:443-460, 1999. Keyword(s): neural networks, mixture of experts, two-group classification. [bibtex-entry]

  116. I. Morlini. Radial basis function networks with partially classified data. Ecological Modelling, 120:109-118, 1999. Keyword(s): classification, discriminant analysis, mixture analysis, radial basis function networks. [bibtex-entry]

  117. Z. Pawlak. Rough classification. International Journal of Human-Computer Studies, 51:369-383, 1999. [bibtex-entry]

  118. W. Penny and S. Roberts. Bayesian neural networks for classification: How useful is the evidence framework?. Neural Networks, 12:877-892, 1999. Keyword(s): classification, multi-layer perception, bayesian, regularization, feature selection, model selection, committees. [bibtex-entry]

  119. J. Ruiz-Shulcloper and M. Lazo-Cortés. Mathematical algoritms for the supervised classification based on fuzzy partial precedence. Mathematical and Computer Modelling, 29:111-119, 1999. Keyword(s): fuzzy patern recognition problems, fuzzy supervised classification, partial precedence. [bibtex-entry]

  120. Y. Shapira and I. Gath. Feature selection for multiple binary classification problems. Pattern Recognition Letters, 20:823-832, 1999. Keyword(s): feature selection, transpose projection, alternative partitions, clustering. [bibtex-entry]

  121. Y. Smith, G. Zajicek, M. Werman, G. Pizov, and Y. Sherman. Similarity measurement method for the classification of architectural differentiated images. Computers and Biomedical Research, 32:1-12, 1999. [bibtex-entry]

  122. N. Yanev and S. Balev. A Combinatorial approach to the classification problem. European Journal of Operational Research, 115:339-350, 1999. Keyword(s): classification, branch and bound, heuristics. [bibtex-entry]

  123. M. Zadeh and P. Nassery. Application of quadratic neural networks to seismic signal classification. Physics on the Earth and Planetary Interiors, 113:103-110, 1999. Keyword(s): neural networks, classification, Prony method, ARMA model. [bibtex-entry]

  124. R. Östermark. A fuzzy neural network algorithm for multigroup classification. Fuzzy Sets and Systems, 105(1):113-122, 1999. Keyword(s): artificial intelligence, multicriteria analysis, pattern recognition, hybrid fuzzy neural networks, Fuzzy set theory, multigroup classification. [bibtex-entry]

  125. P. Allaart. Minimax risk inequalities for the location-parameter classification problem. Journal of Multivariate Analysis, 66:255-269, 1998. Keyword(s): optimal-partioning, minimax risk, classification, partition range, convexity theorem, concentration function, tail concentration. [bibtex-entry]

  126. B. Derriks and D. Willems. Negative feedback in information dialogues: Identification, classification and problem- solving procedures. International Journal of Human-Computer Studies, 48:577-604, 1998. [bibtex-entry]

  127. A. Gonzalez and R. Perez. Completeness and consistency conditions for learning fuzzy rules. Fuzzy Sets and Systems, 96:37-51, 1998. Keyword(s): machine learning, classification, fuzzy logic, fuzzy rules, genetic algorithm. [bibtex-entry]

  128. H. Guvenir and E. Erel. Multicriteria inventory classification using a genetic algorithm. European Journal of Operational Research, 105:29-37, 1998. Keyword(s): computers, genetic algorithm, AHP, inventory, multi-criteria analysis. [bibtex-entry]

  129. M. Horváth and G. Lugosi. Scale-sensitive dimensions and skeleton estimates for classification. Discrete Applied Mathematics, 85:37-61, 1998. [bibtex-entry]

  130. H. Ishibuchi, T. Murata, and M. Gen. Performance evaluation of fuzzy rule-based classification systems obtained by multi- objective genetic algorithms. Computers & Industrial Engineering, 35(3-4):575-578, 1998. Keyword(s): fuzzy rule-based system, pattern classification, rule selection, genetic algorithm, knowledge acquisition. [bibtex-entry]

  131. S. Kundu and A. Martinsek. Using a stopping rule to determine the size of the training sample in a classification problem. Statistics & Probability Letters, 37:19-27, 1998. Keyword(s): classification, discrimination, pattern recognition, density estimate, stopping rule. [bibtex-entry]

  132. O. Larichev, H. Moshkovich, and S. Rebrik. Systematic research into human behavior in multiattribute object classification problems. Acta Psychologica, 68:171-182, 1998. [bibtex-entry]

  133. D. Magennis, E. Watts, and S. Wright. Convertible notes: The debt versus equity classification problem. Journal of Multinational Financial Management, 8:303-315, 1998. Keyword(s): convertible notes, signalling, event study. [bibtex-entry]

  134. N. Maglaveras, T. Stamkopoulos, K. Diamantaras, C. Papas, and M. Strintzis. ECG pattern recognition and classification using non-linear transformations and neural networks: A review. International Journal of Medical Informatics, 52:191-208, 1998. Keyword(s): biomedical signal processing, ECG processing, non-linear principal component analysis, neural networks, ischemia detection. [bibtex-entry]

  135. P. Perny. Multicriteria filtering methods based on concordance and non-discordance principles. Annals of Operations Research, 80:137-165, 1998. Keyword(s): multicriteria decision support, preference modelling, classification, valued binary relations, fuzzy sets. [bibtex-entry]

  136. C. Zopounidis and M. Doumpos. Developing a multicriteria decision support system for financial classification problems: The FINCLAS system. Optimization Methods and Software, 8(3-4):277-304, 1998. [bibtex-entry]

  137. R. Östermark and R. Höglund. Addressing the multigroup discriminant problem using multivariate statistics and mathematical programmning. European Journal of Operational Research, 108:224-237, 1998. Keyword(s): classification, mathematical programming, multivariate statistics, Monte Carlo simulations. [bibtex-entry]

  138. O. Asparoukhov and A. Stam. Mathematical programming formulations for two-group classification with binary variables. Annals of Operations Research, 74:89-112, 1997. Keyword(s): binary variables, classification analysis, discriminant analysis, linear programming, mixed integer programming. [bibtex-entry]

  139. V. Gupta, J.-G. Chen, and M. Murtaza. A learning vector quantization neural network model for the classification of industrial construction projects. Omega - The International Journal of Management Science, 25(6):715-727, 1997. Keyword(s): neural networks, construction industry, application, classification, decision making, learning vectr optimization. [bibtex-entry]

  140. 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]

  141. A. Kehagias and V. Petridis. Predictive modular neural networks for time series classification. Neural Networks, 10(1):31-49, 1997. Keyword(s): modular neural networks, hierarchical neural networks, adaptive neural networks, times series, classification, prediction, Bayesian decision rules. [bibtex-entry]

  142. W. Silvert. Ecological impact classification with fuzzy sets. Ecological Modelling, 96:1-10, 1997. Keyword(s): ecological impact, environmental impact, classification, fuzzy logic, fuzzy set theory. [bibtex-entry]

  143. R. Słowiński, C. Zopounidis, and A. Dimitras. Prediction of company acquisition in Greece by means of the rough set approach. European Journal of Operational Research, 100(1):1-15, 1997. Keyword(s): decision, finance, rough set theory, classification, prediction, company acquisition. [bibtex-entry]

  144. G. Smith and I. Burns. Measuring texture classification algorithms. Pattern Recognition Letters, 18:1495-1501, 1997. Keyword(s): texture features, classification, comparison, metric. [bibtex-entry]

  145. B. Stiles and J. Ghosh. Habituation based neural networks for spatio-temporal classification. Neurocomputing, 15:273-307, 1997. Keyword(s): dynamic neural networks, habituation, classification, spatio-temporal signals, recurrent networks. [bibtex-entry]

  146. A. Vakil. Confronting the classification problem: Toward a taxonomy of NGOs. World Development, 25(12):2057-2070, 1997. [bibtex-entry]

  147. P. Burrascano and D. Pirollo. Improved binary classification performance using an information theoretic criterion. Neurocomputing, 13:375-383, 1996. [bibtex-entry]

  148. I. Fazekas and F. Liese. Some properties od the hellinger transform and its application in classification problems. Computers & Mathematical Applications, 31(8):107-116, 1996. Keyword(s): Hellinger transform, Radon-Nikodym derivative, multidimensional Gaussian autoregressive process, Ornstein-Uhlenbeck process. [bibtex-entry]

  149. K. Lam, E. Choo, and J. Moy. Minimizing deviations from the group mean: A new linear programming approach for the two-group classification problem. European Journal of Operational Research, 88:358-367, 1996. Keyword(s): classification, linear programming, multivariate statistics. [bibtex-entry]

  150. A. Mechitov, H. Moshkovich, J. Bradley, and R. Schellenberger. An ordinal model for case-based reasoning in a classification task. International Journal of Expert Systems: Research and Applications, 9(2):225-242, 1996. [bibtex-entry]

  151. S. Olariu and N. Rao. Simple algoritms for some classification problems. Pattern Recognition Letters, 17:163-167, 1996. Keyword(s): classification, pattern recognition, partitions, equivalence relations, refinement. [bibtex-entry]

  152. P. Smyth. Bounds on the mean classification error rate of multiple experts. Pattern Recognition Letters, 17:1253-1257, 1996. Keyword(s): classification, multiple experts, remote-sensing, planetary geology. [bibtex-entry]

  153. P. Wanarat and R. Pavur. Examining the effect of second-order terms in mathematical programming approaches to the classification problem. European Journal of Operational Research, 93:582-601, 1996. Keyword(s): mathematical programming, linear programming, mixed integer programming, discriminant analysis. [bibtex-entry]

  154. J. Wilson. Integer programming formulations of statistical classification problems. Omega - The International Journal of Management Science, 24(6):681-688, 1996. Keyword(s): mathematical programming, classification. [bibtex-entry]

  155. B. Fagot. Classification of problem behaviors in young children: A comparison of four systems. Journal of Applied Development Psychology, 16:95-106, 1995. [bibtex-entry]

  156. A. Stam and D. Ungar. RAGNU: A microcomputer package for two-group mathematical programming-based nonparametric classification. European Journal of Operational Research, 86:374-388, 1995. Keyword(s): two-group classification analysis, computer software for satistical analysis. [bibtex-entry]

  157. M. Tanaka, N. Aoyama, A. Sugiura, and Y. Koseki. Integration of multiple knowledge representation for classification problems. Artificial Intelligence in Engineering, 9:243-251, 1995. Keyword(s): multiple knowledge representation, classification, knowledge base architecture, AI tool. [bibtex-entry]

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  159. A. Mechitov, H. Moshkovich, and D. Olson. Problems of decision rule elicitation in a classification task. Decision Support Systems, 12(2):115-126, 1994. [bibtex-entry]

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  161. S. Chatterjee and V. Srinivasan. Graphical analysis and financial classification: A case study. Managerial and Decision Economics, 13(6):527-537, 1992. [bibtex-entry]

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Conference articles
  1. L. Denoeud, I. Charon, A. Guénoche, and O. Hudry. Classes empiétantes dans un graphe e application aux interactions entre protéines. In J.-C. Billalit and C. Esswein, editors, ROADEF'05 - 6ème Congrès, volume 1, France, pages 393-408, 2005. Société Française de Recherche Opérationnelle et d'Aide à la Décision, Presses Universitaires François Rabelais. Keyword(s): bio-informatique, classification, graphe d'interactions. [bibtex-entry]

  2. M. Doumpos and C. Zopounidis. An outranking relation approach for classification problems based on pairwise comparisons. In C. Henggeler Antunes, J. Figueira, and J. N. Clímaco, editors, Proceedings of the 56th Meeting of the European Working Group ``Multiple Criteria Decision Aiding'', Coimbra, October 3-5, 2002, Portugal, pages 67-84, 2004. CCDRC, INESC Coimbra, Faculty of Economics of the University of Coimbra. Keyword(s): multicriteria decision aid, classification, outranking relations, linear programming. [bibtex-entry]

  3. M. Doumpos and C. Zopounidis. An outranking relation approach for classification problems based on pairwise comparisons. In J. Figueira, C. Henggeler Antunes, and J. N. Clímaco, editors, 56th Meeting of the European Working Group ``Multiple Criteria Decision Aiding'', Coimbra, October 3-5, Portugal, 2002. Faculdade de Economia da Universidade de Coimbra, INESC Coimbra, FEUC Printing Service. [bibtex-entry]

  4. A. Guitouni, B. Brisset, L. Belfares, K. Tiliki, N. Belacel, and C. Poirier. Automatic documents analyzer and classification. In 7th International Command and Control Research and Technology Symposium, 2002. [bibtex-entry]

  5. N. Belacel. Une approche du choix flou pour les probèmes de classification multicritère. In Rencontres Francophones sur la logique floue et ses applications, France, pages 37-44, 2000. La Rochelle, CEPADUS-Editions. Keyword(s): multicriteria decision aid, classification, fuzzy sets, scoring function, medical diagnosis. [bibtex-entry]

  1. X. Wang. Country Risk Classification and Multicriteria Decision-Aid. Master's thesis, McMaster University, Hamilton, Ontario, 2004. [bibtex-entry]

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