Skip to main content
SpringerLink
Log in

Multifactor Modelling with Regularization

  • Conference paper
  • First Online:
Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9883))

  • 1327 Accesses

Abstract

In this paper a multifactor modeling software system is described for building of a polynomial formula by a genetic algorithm. Thus a target variable is modeled by a subset of available explanatory variables represented as discrete time series. The proposed approach is improved by regularization in order to avoid the problem of overfitting.

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Hamilton, J.: Time Series Analysis. Princeton University Press, Princeton (1994)

    Google Scholar 

  2. Koza, J.: Genetic Programming. MIT Press, Cambridge (1992)

    Google Scholar 

  3. Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press, Cambridge (1999)

    Google Scholar 

  4. Rosen, K.: Discrete Mathematics and Its Applications, 4th edn. AT&T (1998)

    Google Scholar 

  5. Rosenberg, A.: Machine Learning Lectures, CUNY Graduate Center (2009). (http://eniac.cs.qc.cuny.edu/andrew/gcml/lecture5.pdf)

Download references

Author information

Authors and Affiliations

  1. EuroRisk Systems Ltd., Varna, Bulgaria

    Ventsislav Nikolov

Authors
  1. Ventsislav Nikolov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ventsislav Nikolov .

Editor information

Editors and Affiliations

  1. Winston-Salem State University, Winston Salem, North Carolina, USA

    Christo Dichev

  2. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Gennady Agre

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Nikolov, V. (2016). Multifactor Modelling with Regularization. In: Dichev, C., Agre, G. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2016. Lecture Notes in Computer Science(), vol 9883. Springer, Cham. https://doi.org/10.1007/978-3-319-44748-3_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-44748-3_38

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44747-6

  • Online ISBN: 978-3-319-44748-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation