Abstract
This paper presents the problem of building the decision scheme in the multistage pattern recognition task. This task can be presented using a decision tree. This decision tree is built in the learning phase of classification. This paper proposes a split criterion based on the analysis of the confusion matrix. Specifically, we propose the division associated with an incorrect classification. The obtained results were verified on the data sets form UCI Machine Learning Repository and one real-life data set of the computer-aided medical diagnosis.
Chapter PDF
Similar content being viewed by others
References
Kołakowska, A., Malina, W.: Fisher Sequential Classifiers. IEEE Transaction on Systems, Man, and Cybernecics – Part B Cybernecics 35(5), 988–998 (2005)
Mui, J., Fu, K.S.: Automated classification of nucleated blood cells using a binary tree classifier. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-2, 429–443 (1980)
Podolak, I.T.: Hierarchical classifier with overlapping class groups. Expert Syst. Appl. 34(1), 673–682 (2008)
Safavian, S.R., Landgrebe, D.: A survey of decision tree classifier methodology. IEEE Trans. Systems, Man Cyber. 21(3), 660–674 (1991)
Penar, W., Woźniak, M.: Experiments on classifiers obtained via decision tree induction methods with different attribute acquisition cost limit. Advances in Soft Computing 45, 371–377 (2007)
Quinlan, J.R.: Induction on Decision Tree. Machine Learning 1, 81–106 (1986)
Manwani, N., Sastry, P.S.: Geometric decision tree. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 42(1), 181–192 (2012)
Kurzyński, M.: Decision Rules for a Hierarchical Classifier. Pat. Rec. Let. 1, 305–310 (1983)
Woźniak, M.: A hybrid decision tree training method using data streams. Knowledge and Information Systems 29(2), 335–347 (2010)
Choraś, M.: Image feature extraction methods for ear biometrics–A survey. In: 6th International Conference on Computer Information Systems and Industrial Management Applications, CISIM 2007, pp. 261–265. IEEE (2007)
Choraś, R.S.: Content-based retrieval using color, texture, and shape information. In: Progress in Pattern Recognition, Speech and Image Analysis, pp. 619–626 (2003)
Guyon, I., Elisseeff, A.: An introduction to variable and feature selection. The Journal of Machine Learning Research 3, 1157–1182 (2003)
Rejer, I.: Genetic Algorithms in EEG Feature Selection for the Classification of Movements of the Left and Right Hand. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds.) CORES 2013. AISC, vol. 226, pp. 579–589. Springer, Heidelberg (2013)
Burduk, R., Zmyślony, M.: Decomposition of classification task with selection of classifiers on the medical diagnosis example. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, S.-B. (eds.) HAIS 2012, Part II. LNCS, vol. 7209, pp. 569–577. Springer, Heidelberg (2012)
Burduk, R.: Classification error in Bayes multistage recognition task with fuzzy observations. Pattern Analysis and Applications 13(1), 85–91 (2010)
Kurzyński, M.: On the Multistage Bayes Classifier. Pattern Recognition 21, 355–365 (1988)
Berger, J.: Statistical Decision Theory and Bayesian Analysis. Springer, New York (1993)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. John Wiley and Sons (2000)
Frank, A., Asuncion, A.: UCI machine learning repository (2010)
Burduk, R., Woźniak, M.: Different decision tree induction strategies for a medical decision problem. Central European Journal of Medicine 7(2), 183–193 (2010)
Kurzyński, M.: Diagnosis of acute abdominal pain using three-stage classifier. Computers in Biology and Medicine 17(1), 19–27 (1987)
Trawiński, B., Smetek, M., Telec, Z., Lasota, T.: Nonparametric statistical analysis for multiple comparison of machine learning regression algorithms. International Journal of Applied Mathematics and Computer Science 22(4), 867–881 (2012)
Demšar, J.: Statistical comparisons of classifiers over multiple data sets. The Journal of Machine Learning Research 7, 1–30 (2006)
Bobrowski, L., Topczewska, M.: Separable Linearization of Learning Sets by Ranked Layer of Radial Binary Classifiers. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds.) CORES 2013. AISC, vol. 226, pp. 131–140. Springer, Heidelberg (2013)
MacArthur, R.: On the relative abundance of bird species. Proc. Natl. Acad. Sci. USA 43, 293–295 (1957)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 IFIP International Federation for Information Processing
About this paper
Cite this paper
Burduk, R., Trajdos, P. (2013). Construction of Sequential Classifier Using Confusion Matrix. In: Saeed, K., Chaki, R., Cortesi, A., Wierzchoń, S. (eds) Computer Information Systems and Industrial Management. CISIM 2013. Lecture Notes in Computer Science, vol 8104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40925-7_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-40925-7_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40924-0
Online ISBN: 978-3-642-40925-7
eBook Packages: Computer ScienceComputer Science (R0)