Abstract
A priori information about selected pattern recognition problem is often a necessary precondition to reach a sufficient quality of the problem solution. Such information could take the form of the ranked order in the referencing sets of objects or events. For example, we can encounter a case when one patient is suffering from a more advanced stage of a disease than the another one. In other cases, we can assume that some events took place earlier or later than the regarded one. A ranked regression task is aimed at designing such linear transformation of multivariate data sets on the line which preserves with the highest precision possible the ranked order. The convex and piecewise linear (CPL) criterion functions are used here for designing ranked linear models.
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References
Duda OR and Hart PE, Stork DG (2000) Pattern Classification, J. Wiley, New York
Fukunaga K (1990) Statistical Pattern Recognition, Academic Press, Inc., San Diego
Bobrowski L (1996) Piecewise-Linear Classifiers, Formal Neurons and separability of the Learning Sets. In: Proceedings of ICPR’96, pp. 224–228, (13th International Conference on Pattern Recognition, August 25–29, 1996, Vienna, Austria)
Bobrowski L, Wasyluk H (2001) Diagnosis supporting rules of the Hepar system, pp. 1309–1313 In: MEDINFO 2001, Petel VL, Rogers R, Haux R (eds), IOS Press, Amsterdam
Bobrowski L and Niemiro W(1984) A method of synthesis of linear discriminant function in the case of nonseparabilty. Pattern Recognition 17:205–210
Bobrowski L, Topczewska M (2003) Tuning of diagnosis support rules through visualizing data transformations, pp. 15–23. In: Medical Data Analysis, Perner P et al. (eds), Springer-Verlag, Berlin
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Bobrowski, L. (2005). Linear Ranked Regression - Designing Principles. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_10
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DOI: https://doi.org/10.1007/3-540-32390-2_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
Online ISBN: 978-3-540-32390-7
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