Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Parametric Data Reduction Techniques

  • Rui ZhangEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_547


A parametric data reduction technique is a data reduction technique that assumes a certain model for the data. The model contains some parameters and the technique fits the data into the model to determine the parameters. Then data reduction can be performed.

Key Points

Parametric data reduction (PDR) techniques is opposite to nonparametric data reduction (NDR) techniques. A model with parameters is used in a PDR technique and therefore some computation is required to determine these parameters, which may be costly. However, if a PDR technique is well-chosen, it may result in much more data reduction than NDR techniques. A representative example is linear regression [ 3]. Linear regression assumes that the data fall on a straight line, expressed by the following formula
$$ \mathrm{Y}=\mathrm{a}+\mathrm{bX} $$
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Recommended Reading

  1. 1.
    Barbará D, DuMouchel W, Faloutsos C, Haas PJ, Hellerstein JM, Ioannidis YE, Jagadish HV, Johnson T, Ng RT, Poosala V, Ross KA, Sevcik KC. The New Jersey data reduction report. IEEE Data Eng Bull. 1997;20(4):3–45.Google Scholar
  2. 2.
    Jolliffe IT. Principal component analysis. Berlin: Springer; 1986.zbMATHCrossRefGoogle Scholar
  3. 3.
    Wonnacott RJ, Wonnacott TH. Introductory statistics. New York: Wiley; 1985.zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of MelbourneMelbourneAustralia
  2. 2.Dataware VenturesTucsonUSA
  3. 3.Dataware VenturesRedondo BeachUSA

Section editors and affiliations

  • Xiaofang Zhou
    • 1
  1. 1.School of Inf. Tech. & Elec. Eng.Univ. of QueenslandBrisbaneAustralia