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Abad,P. L. & Banks, W. J. (1993). New LP based heuristics for the classification problem. European Journal of Operations Research, 67, 88–100.
Bhattacharyya, S. & Pendharkar, P. C. (1998). Inductive evolutionary and neural techniques for discrimination. Decision Sciences, 29, 871–899.
Doi, K.,Giger, M. L.,Mishikawa, R. M.,Hoffmann, K. R.,Macmahon, H.,Schmidt, R. A., & Chua, K. G. (1993). Digital radiography: A useful clinical tool for computer-aided diagnosis by quantitative analysis of radiographic images. Acta Radiologica, 34, 426–439.
Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, 179–188.
Goldberg, D. E. & Deb, K. (1991). A comparative analysis of selection schemes used in genetic algorithms. In G. Rawlins (Ed.), Foundations of Genetic Algorithms, (pp. 69–93) San Mateo, CA: Morgan Kaufmann.
Joachimsthaler, E. A. & Stam, A. (1988). Four approaches to the classification problem in discriminant analysis: An experimental study. Decision Sciences, 19, 322–333.
King, R. D.,Henry, R.,Feng, C., & Sutherland, A. (1994). A comparative study of classification algorithms: Statistical, machine learning and neural network. In K. Furukawa, D. Michie, & S. Muggleton (Eds.), Machine Intelligence, 13: Machine Intelligence and Inductive Learning, Oxford: Clarendon Press.
Koehler, G. J. (1991). Linear discriminant functions determined by genetic search. ORSA Journal on Computing, 3, 345–357.
Koehler, G. J. & Erenguc, S. S. (1990). Minimizing misclassifications in linear discriminant analysis. Decision Sciences, 21, 63–85.
Kovalerchuck, B.,Triantaphyllou, E.,Ruiz, J. F., & Clayton, J. (1997). Fuzzy logic in computer-aided breast cancer diagnosis: Analysis of lobulation. Artificial Intelligence in Medicine, 11, 75–85.
Pendharkar, P. C.,Rodger, J. A.,Yaverbaum, G. J.,Herman, N., & Benner, M. (1999). Association, statistical, mathematical, and neural approaches for mining breast cancer patterns. Expert Systems with Applications, 17, 223–232.
Turney, P. D. (1995). Cost-sensitive classification: Empirical evaluation of a hybrid genetic decision tree induction algorithm. Journal of Artificial Intelligence Research, 2, 369–409.
Wu, Y.,Doi, K.,Giger, M.,Metz, C., & Zhang, W. (1994). Reduction of false positive in computerized detection of lung nodules in chest radiographs using artificial neural networks, discriminant analysis and a rule-based scheme. Journal of Digital Imaging, 17, 196–207.
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