Skip to main content
SpringerLink
Log in

The quick dynamic clustering method for mixed-type data

  • Control Systems and Information Technologies
  • Published:
Automation and Remote Control Aims and scope Submit manuscript

Abstract

This paper describes a new approach to high-dimensional mixed-type data clustering with missing values, which combines information on common nearest neighbors with classic between-vectors distances calculated by an original technique. The results are applied to form intersecting clusters for every missing value.

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

Access this article

Log in via an institution

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. Little, R.J.A. and Rubin, D.B., Statistical Analysis with Missing Data, New Jersey: Wiley, 2002, 2nd ed.

    MATH  Google Scholar 

  2. Ayuyev, V.V., Aung, Z.Y., and Thein, Ch.M., The Domain Compensation Method for Incomplete Information in a Database, in Tr. Mosk. Gos. Tekhn. Univ., Moskow: Gos. Tekhn. Univ., 2007, vol. 2, pp. 57–64.

    Google Scholar 

  3. Fujikawa, Y. and Ho, T.B., Cluster-based Algorithms for Dealing with Missing Values, in Proc. in Advances in Knowledge Discovery and Data Mining, Berlin: Springer, 2002, pp. 549–554.

    Google Scholar 

  4. Mantaras, R.L., A Distance-based Attribute Selection Measure for Decision Tree Induction, Mach. Learn., 1991, vol. 6, pp. 81–92.

    Article  Google Scholar 

  5. Tan, P.N., Steinbach, M., and Kumar, V., Introduction to Data Mining, New York: Addison-Wesley, 2005.

    Google Scholar 

  6. Gan, G., Ma, C., and Wu, J., Data Clustering: Theory, Algorithms, and Applications, in ASA-SIAM Series on Statistics and Applied Probability, Philadelphia: SIAM, 2007, vol. 20, p. 466.

    Google Scholar 

  7. Wishart, D., K-means Clustering with Outlier Detection, Mixed Variables and Missing Values, in Exploratory Data Analysis in Empirical Research, Schwaiger, M. and Opitz, O., Eds., New York: Springer, 2003, pp. 216–226.

    Chapter  Google Scholar 

  8. Ayuyev, V.V., Thura, A., Hlaing, N.N., and Loginova, M.B., A Modification of the Static Clustering Method for Operation with Inconnected Data, in Tr. Mosk. Gos. Tekhn. Univ., Moskow: Gos. Tekhn. Univ., 2008, vol. 2, pp. 86–93.

    Google Scholar 

  9. Asuncion, A. and Newman, D.J., UCI Machine Learning Repository, Irvine: Univ. of California, School of Inf. and Computer Sci., 2008.

    Google Scholar 

  10. Ertoz, L., Steinback, M., and Kumar, V., Finding Clusters of Different Sizes, Shapes, and Density in Noisy High-dimensional Data, Second SIAM Int. Conf. on Data Mining, San Francisco: SIAM, 2003, pp. 47–58.

    Google Scholar 

  11. Schafer, J.L., Multiple Imputation: A Primer, Statist. Meth. Medical Res., 1999, vol. 8, no. 1, pp. 3–15.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Kaluga Branch of Bauman Moscow State Technical University, Kaluga, Russia

    V. V. Ayuyev, A. Thura, N. N. Hlaing & M. B. Loginova

Authors
  1. V. V. Ayuyev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Thura
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N. N. Hlaing
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. B. Loginova
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Original Russian Text © V.V. Ayuyev, A. Thura, N.N. Hlaing, M.B. Loginova, 2008, published in Sistemy Upravleniya i Informatsionnye Tekhnologii, 2008, No. 3, pp. 26–29.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ayuyev, V.V., Thura, A., Hlaing, N.N. et al. The quick dynamic clustering method for mixed-type data. Autom Remote Control 73, 2083–2088 (2012). https://doi.org/10.1134/S0005117912120120

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0005117912120120

Keywords

Search

Navigation