Skip to main content
SpringerLink
Log in

PCA Based Oblique Decision Rules Generating

  • Conference paper
Adaptive and Natural Computing Algorithms (ICANNGA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7824))

Included in the following conference series:

Abstract

The paper presents the new algorithm of oblique rules induction. On the basis of the initial step that consists in clustering the decision class into subclasses, for every subclass the oblique hypercuboid is generated. Sides of the hypercuboid are parallel and perpendicular to the directions defined by PCA. One hypercuboid corresponds to one decision rule. Results of inducting rules in the new way were compared with other oblique and non-oblique rules sets built on the artificial and real data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bazan, J., Szczuka, M.S., Wróblewski, J.: A New Version of Rough Set Exploration System. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds.) RSCTC 2002. LNCS (LNAI), vol. 2475, pp. 397–404. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  2. Bennett, K.P., Blue, J.A.: A support vector machine approach to decision trees. In: Proceedings of the IJCNN 1998, pp. 2396–2401 (1997)

    Google Scholar 

  3. Bloedorn, E., Michalski, R.S.: Data-Driven Constructive Induction. IEEE Intelligent Systems and Their Application 13(2), 30–37 (1998)

    Article  Google Scholar 

  4. Cantu-Paz, E., Kamath, C.: Using evolutionary algorithms to induce oblique decision trees. In: Proc. of Genetic and Evolutionary Computation Conference, pp. 1053–1060 (2000)

    Google Scholar 

  5. Frank, A., Asuncion, A.: UCI Machine Learning Repository (2010), http://archive.ics.uci.edu/ml

  6. Frank, E., Witten, I.H.: Generating Accurate Rule Sets Without Global Optimization. In: Proc. of the 15th International Conference on Machine Learning, pp. 144–151 (1998)

    Google Scholar 

  7. Kim, H., Loh, W.-Y.: Classification trees with bivariate linear discriminant node models. Journal of Computational and Graphical Statistics 12, 512–530 (2003)

    Article  MathSciNet  Google Scholar 

  8. Latkowski, R., Mikołajczyk, M.: Data Decomposition and Decision Rule Joining for Classification of Data with Missing Values. In: Peters, J.F., Skowron, A., Grzymała-Busse, J.W., Kostek, B.z., Swiniarski, R.W., Szczuka, M.S. (eds.) Transactions on Rough Sets I. LNCS, vol. 3100, pp. 299–320. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  9. Michalak, M., Sikora, M., Ziarnik, P.: ORG - Oblique Rules Generator. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS, vol. 7268, pp. 152–159. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  10. Murthy, S.K., Kasif, S., Salzberg, S.: A system for induction of oblique decision trees. Journal of Artificial Intelligence Research 2, 1–32 (1994)

    MATH  Google Scholar 

  11. Pindur, R., Sasmuga, R., Stefanowski, J.: Hyperplane Aggregation of Dominance Decision Rules. Fundamenta Informaticae 61(2), 117–137 (2004)

    MathSciNet  MATH  Google Scholar 

  12. Raś, Z.W., Daradzińska, A., Liu, X.: System ADReD for discovering rules based on hyperplanes. Engineering Applications of Artificial Intelligence 17(4), 401–406 (2004)

    Article  Google Scholar 

  13. Ripley, B.D.: Pattern Recognition and Neural Networks. Cambridge University Press (1996)

    Google Scholar 

  14. Sikora, M.: An algorithm for generalization of decision rules by joining. Foundation on Computing and Decision Sciences 30(3), 227–239 (2005)

    MATH  Google Scholar 

  15. Sikora, M.: Induction and pruning of classification rules for prediction of microseismic hazards in coal mines. Expert Systems with Applications 38(6), 6748–6758 (2011)

    Article  MathSciNet  Google Scholar 

  16. Sikora, M., Gudyś, A.: CHIRA – Convex Hull Based Iterative Algorithm of Rules Aggregation. Fundamenta Informaticae 123(2), 143–170 (2013)

    Google Scholar 

  17. Smith, L.I.: A tutorial on Principal Components Analysis (2002), http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf

  18. Ślęzak, D., Wróblewski, J.: Classification Algorithms Based on Linear Combinations of Features. In: Żytkow, J.M., Rauch, J. (eds.) PKDD 1999. LNCS (LNAI), vol. 1704, pp. 548–553. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland

    Marcin Michalak & Karolina Nurzyńska

  2. SOMAR S.A., ul. Karoliny 4, 40-186, Katowice, Poland

    Marcin Michalak

Authors
  1. Marcin Michalak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karolina Nurzyńska
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Départment des Systémes d’Information, Quartier UNIL-Dorigny, Bâtiment Internef, Université de Lausanne, 105, Lausanne, Switzerland

    Marco Tomassini , Alberto Antonioni , Fabio Daolio  & Pierre Buesser , ,  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Michalak, M., Nurzyńska, K. (2013). PCA Based Oblique Decision Rules Generating. In: Tomassini, M., Antonioni, A., Daolio, F., Buesser, P. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2013. Lecture Notes in Computer Science, vol 7824. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37213-1_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37213-1_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37212-4

  • Online ISBN: 978-3-642-37213-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation