Abstract
We propose and discuss improved classification rules when a subset of the predictors is known to be ordered. We compare the performance of the new rules with other standard rules in a restricted normal setting using simulation experiments and real data exposing their good performance.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Abelson, R.P., Tukey, J.W.: Efficient utilization of non-numerical information in quantitative analysis: general theory and the case of the simple order. Ann. Math. Stat. 34, 1347–1369 (1963)
Attallah, A., Toson, E., El-Waseef, A., Abo-Seif, M., Omran, M., Shiha, G.: Discriminant function based on hyaluronic acid and its degrading enzymes and degradation products for differentiating cirrhotic from non-cirrhotic liver diseased patients in chronic HCV infection. Clin. Chim. Acta. 369, 66–72 (2006)
Blake, C.L., Merz, C.J.: UCI Repository Learning Databases. University of California, Department of Information and Computer Science, Irvine, CA. http://www.ics.uci.edu/~mlearn/MLRepository.html (1998)
Fernández, M.A., Rueda, C., Salvador, B.: Incorporating additional information to normal linear discriminant rules. J. Am. Stat. Assoc. 101, 569–577 (2006)
Long, T., Gupta, R.D.: Alternative linear classification rules under order restrictions. Commun. Stat. Theory Methods 27, 559–575 (1998)
Rueda,C., Fernández, M.A., Salvador, B.: Bayes discriminant rules with ordered predictors. J. Classification 26, 201–225 (2009)
Van Eeden, C.: Restricted Parameter Space Estimation Problems. Springer, New York, NY (2006)
Acknowledgments
Research partially supported by Spanish DGES grant MTM2009-11161.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fernández, M., Rueda, C., Salvador, B. (2011). Efficient Incorporation of Additional Information to Classification Rules. In: Fichet, B., Piccolo, D., Verde, R., Vichi, M. (eds) Classification and Multivariate Analysis for Complex Data Structures. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13312-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-13312-1_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13311-4
Online ISBN: 978-3-642-13312-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)