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]



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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]

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]



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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]



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