Parametric Data Reduction Techniques
- Rui Zhang
- … show all 1 hide
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.
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 . Linear regression assumes that the data fall on a straight line, expressed by the following formula
- Barbará D., DuMouchel W., Faloutsos C., Haas P.J., Hellerstein J.M., Ioannidis Y.E., Jagadish H.V., Johnson T., Ng R.T., Poosala V., Ross K.A., and Sevcik K.C. The New Jersey data reduction report. IEEE Data Eng. Bull., 20(4):3–45, 1997.
- Jolliffe I.T. Principal Component Analysis. Springer, Berlin, 1986.
- Wonnacott R.J. and Wonnacott T.H. Introductory Statistics. Wiley, New York, 1985.
- Parametric Data Reduction Techniques
- Reference Work Title
- Encyclopedia of Database Systems
- pp 2044-2045
- Print ISBN
- Online ISBN
- Springer US
- Copyright Holder
- Springer US
- Additional Links
- Industry Sectors
- eBook Packages
- Editor Affiliations
- 1. College of Computing, Georgia Institute of Technology
- 2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo
- Rui Zhang (1)
- Author Affiliations
- 1. University of Melbourne, Melbourne, VIC, Australia
To view the rest of this content please follow the download PDF link above.