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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1999 Working Papers
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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1999 Working Papers
      • View Item
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      Pace Regression

      Wang, Yong; Witten, Ian H.
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      Wang, Y. & Witten, I.H. (1999). Pace Regression. (Working paper 99/12). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
      Permanent Research Commons link: https://hdl.handle.net/10289/1041
      Abstract
      This paper articulates a new method of linear regression, “pace regression”, that addresses many drawbacks of standard regression reported in the literature-particularly the subset selection problem. Pace regression improves on classical ordinary least squares (OLS) regression by evaluating the effect of each variable and using a clustering analysis to improve the statistical basis for estimating their contribution to the overall regression. As well as outperforming OLS, it also outperforms-in a remarkably general sense-other linear modeling techniques in the literature, including subset selection procedures, which seek a reduction in dimensionality that falls out as a natural byproduct of pace regression. The paper defines six procedures that share the fundamental idea of pace regression, all of which are theoretically justified in terms of asymptotic performance. Experiments confirm the performance improvement over other techniques.
      Date
      1999-09
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      99/12
      Publisher
      Computer Science, University of Waikato
      Collections
      • 1999 Working Papers [16]
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