Advertisement

Binary Matrix Pseudo-division and Its Applications

  • Aleš Keprt
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 237)

Abstract

The benefit of each key algorithm also depends on many additional supporting algorithms it uses. It turned out that class of problems related to dimensionality reduction of binary spaces used for statistical analysis of binary data, e.g. binary (Boolean) factor analysis, is dependent on the possibility and ability of performing pseudo-division of binary matrices. The paper presents novelty computation approach to it, giving an algorithm for reasonably fast exact solution.

Keywords

Binary Factor Analysis BFA matrix division factor 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Húsek, D., Frolov, A.A., Řezanková, H., Snášel, V., Keprt, A.: O jednom neuronovém přístupu k redukci dimenze. In: Znalosti 2004, Brno, Czech Republic. VŠB – Technical University of Ostrava, Czech Republic (2004) ISBN 80-248-0456-5Google Scholar
  2. 2.
    Keprt, A.: Using Blind Search and Formal Concepts for Binary Factor Analysis. In: Dateso 2004 – Proceedings of 4th Annual Workshop, Desná-Černá Říčka, Czech Republic, pp. 120–131. VŠB – Technical University of Ostrava, Czech Republic, CEUR WS – Deutsche Bibliothek, Aachen (2004) ISBN 80-248-0457-3, ISSN 1613-0073Google Scholar
  3. 3.
    Keprt, A.: Algorithms for Binary Factor Analysis. Doctoral thesis, VŠB Technical University of Ostrava (2006)Google Scholar
  4. 4.
    Keprt, A., Snášel, V.: Binary Factor Analysis with Help of Formal Concepts. In: Snášel, V., Bělohlávek, R. (eds.) CLA 2004 – Concept Lattices and their Applications, pp. 90–101. VŠB – Technical University of Ostrava, Czech Republic (2004) ISBN 80-248-0597-9Google Scholar
  5. 5.
    Keprt, A., Snášel, V.: Binary Factor Analysis with Genetic Algorithms. In: Proceedings of 4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology – WSTST 2005, Muroran, Japan. Advances in Soft Computing, pp. 1259–1268. Springer, Heidelberg (2005) ISBN 3-540-25055-7, ISSN 1615-3871Google Scholar
  6. 6.
    Mickey, M.R., Mundle, P., Engelman, L.: P8M – Boolean Factor Analysis. In: Dixon, W.J. (ed.) BMDP (Bio-Medical Data Processing) Manual, vol. 2. University of California Press, Berkeley (1990) (see also SPSS at http://www.spss.com/)
  7. 7.
    Sirota, A.M., Frolov, A.A., Húsek, D.: Nonlinear Factorization in Sparsely Encoded Hopfield-like Neural Networks. In: ESANN 1999 Proceedings – European Symposium on Artificial Neural Networks, pp. 387–392. D-Factor Public., Bruges (1999) ISBN 2-600049-9-X Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer Science and Applied MathematicsMoravian University CollegeOlomoucCzech Republic

Personalised recommendations