Measuring Performance in Regression Models

  • Max Kuhn
  • Kjell Johnson

Abstract

When predicting a numeric outcome, some measure of accuracy is typically used to evaluate the model’s effectiveness. However, there are different ways to measure accuracy, each with its own nuance. In Section 5.1 we define common measures for evaluating quantitative performance. We also discuss the concept of variance-bias trade-off (Section 5.2), and the implication of this principle for predictive modeling. In Section 5.3, we demonstrate how measures of predictive performance can be generated in R.

References

  1. Kvålseth T (1985). “Cautionary Note About R 2.” American Statistician, 39(4), 279–285.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Max Kuhn
    • 1
  • Kjell Johnson
    • 2
  1. 1.Division of Nonclinical StatisticsPfizer Global Research and DevelopmentGrotonUSA
  2. 2.Arbor AnalyticsSalineUSA

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