Skip to main content
Log in

Exploratory analysis of benchmark experiments an interactive approach

  • Original Paper
  • Published:
Computational Statistics Aims and scope Submit manuscript

Abstract

Visualization can help a lot to understand the huge amounts of data created in computer simulations and benchmark experiments. In Eugster et al. (Technical report 30, Institut für Statistik, Ludwig-Maximilians-Universität München, Germany 2008) we presented a comprehensive toolbox for exploration and inference on benchmark data, including the bench plot. This plot visualizes the behavior of the algorithms on the individual drawn learning and test samples according to a specific performance measure. In this paper we show that an interactive version of the bench plot can help to uncover details and relations unseen with the static version.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Cook D, Swayne DF (2007) Interactive and dynamic graphics for data analysis: with R and GGobi. Springer, Berlin

    Book  MATH  Google Scholar 

  • Eugster MJA (2010) Benchmark: benchmark experiments toolbox. http://cran.r-project.org/package=benchmark, R package version 0.3

  • Eugster MJA, Hothorn T, Leisch F (2008) Exploratory and inferential analysis of benchmark experiments. Technical Report 30, Institut für Statistik, Ludwig-Maximilians-Universität München, Germany, http://epub.ub.uni-muenchen.de/4134

  • Eugster MJA, Leisch F (2008) Bench plot and mixed effects models: first steps toward a comprehensive benchmark analysis toolbox. In: Brito P (ed) Compstat 2008—proceedings in computational statistics, Physica Verlag, Heidelberg, Germany, pp 299–306

  • Gouberman A, Urbanek S (2008) icp: interactive custom plots—customizable interactive Graphics for R. http://www.rosuda.org/iPlots/, R package version 1.1–0

  • Hothorn T, Leisch F, Zeileis A, Hornik K (2005) The design and analysis of benchmark experiments. J Comput Graph Stat 14(3): 675–699

    Article  MathSciNet  Google Scholar 

  • McNeil DR (1977) Interactive data analysis. Wiley, New York

    Google Scholar 

  • R Development Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org, ISBN 3-900051-07-0

  • Unwin A, Volinsky C, Winkler S (2003) Parallel coordinates for exploratory modelling analysis. Comput Stat Data Analysis 43: 553–564

    Article  MathSciNet  MATH  Google Scholar 

  • Urbanek S (2009) Acinonyx: iPlots extreme. http://www.rforge.net/Acinonyx/, R package version 3.0–0

  • Urbanek S, Theus M (2003) iPlots: high interaction graphics for R. In: Hornik K, Leisch F, Zeileis A (eds) Proceedings of the 3rd international workshop on distributed statistical computing (DSC 2003)

  • Urbanek S, Wichtrey T (2008) iplots: iPlots—interactive graphics for R. http://www.iPlots.org/, R package version 1.1–3

  • Venables W, Ripley B (2002) Modern applied statistics with S, 4th edn. Springer, Berlin

    MATH  Google Scholar 

  • Wickham H (2007) Meifly: models explored interactively. Website ASA sections on statistical computing and graphics (Student Paper Award Winner 2007), available online at http://stat-computing.org/awards/student/winners.html

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Manuel J. A. Eugster.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Eugster, M.J.A., Leisch, F. Exploratory analysis of benchmark experiments an interactive approach. Comput Stat 26, 699–710 (2011). https://doi.org/10.1007/s00180-010-0227-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00180-010-0227-z

Keywords

Navigation