Skip to main content
Log in

Using ε-Nets for Linear Separation of Two Sets in a Euclidean Space R d

  • Published:
Cybernetics and Systems Analysis Aims and scope

Abstract

This paper introduces the concept of -separability. Necessary and sufficient conditions of ε-separability are proved. It is proved that the problem of ε-separability of two sets can be reduced to the trivial problem of separability of their disjoint ε-nets.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. R. A. Fisher, “The use of multiple measurements in taxonomic problems,” Annals of Eugenics, No. 7, 179–188 (1936).

    Article  Google Scholar 

  2. Deng Cai, Xiaofei He, and Jiawei Han, Training Linear Discriminant Analysis in Linear Time, http://researchweb.iiit.ac.in/~nataraj.j/poseSearchReports/icde08_dengcai.pdf.

  3. S. A. Ayvazyan, V. M. Bukhshtaber, I. S. Enyukov, and L. D. Meshalkin, Applied Statistics: Classification and Reduction of Dimensionality [in Russian], Finansy and Statistika, Moscow (1989).

    Google Scholar 

  4. K. V. Vorontsov, Lectures on Statistical (Bayesian) Classification Algorithms [in Russian], http:www.ccas.ru/voron/bdownload/Bayes.pdf.

  5. Chris Fleizach and Satoru Fukushima, A Naive Bayes Classifier on 1998 KDD Cup, http://sysnet.ucsd.edu/~cfleizac/cse250b/project1.pdf.

  6. V. N. Vapnik, The Nature of Statistical Learning Theory, 2nd Ed., Springer, New York (2000).

    Book  MATH  Google Scholar 

  7. V. K. Vorontsov, Lectures on the Method of Support Vectors [in Russian], http://www.ccas.ru/voron/download/SVM.pdf.

  8. Ivor W. Tsang, James T. Kwok, and Pak-Ming Cheung, “Core vector machines: Fast SVM training on very large data sets,” Journal of Machine Learning Research, No. 6, 363–392 (2005).

  9. M. A. Ivanchuk and I. V. Malyk, “Comparison of methods for classification of observations in predicting complications in critically ill patients,” Cybernetics and Systems Analysis, 51, No. 2, 303–312 (2015).

    Article  Google Scholar 

  10. A. M. Raigorodskii, Systems of Common Representatives in Combinatorics and Their Applications in Geometry [in Russian], MTsNMO, Moscow (2009).

    Google Scholar 

  11. L. Dantser, B. Grunbaum, and V. Kli, Helly’s Theorem [Russian translation], Mir, Moscow (1968).

  12. D. Haussler and E. Welzl, “ε-nets and simplex range queries,” Discrete & Computational Geometry, No. 2, 127–151 (1987).

  13. ICS Theory Group. Computational Statistics, https://www.ics.uci.edu/~eppstein/280/cluster.html.

  14. F. Preparata and M. Sheimos, Computational Geometry: Introduction [Russian translation], Mir, Moscow (1989).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. A. Ivanchuk.

Additional information

Translated from Kibernetika i Sistemnyi Analiz, No. 6, November–December, 2015, pp. 147–150.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ivanchuk, M.A., Malyk, I.V. Using ε-Nets for Linear Separation of Two Sets in a Euclidean Space R d . Cybern Syst Anal 51, 965–968 (2015). https://doi.org/10.1007/s10559-015-9789-7

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10559-015-9789-7

Keywords

Navigation