Definition
A nonparametric data reduction technique is a data reduction technique that does not assume any model for the data.
Key Points
Nonparametric data reduction (NDR) techniques is opposite to parametric data reduction (PDR) techniques. A PDR technique must assume a certain model for the data. Parameters of the model are determined before the data reduction is performed. A NDR technique does not assume any model and is applied to the data directly. The data reduction effectiveness of a PDR technique heavily depends on whether the model suits the data well. If well-suited, good accuracy as well as substantial data reduction can be achieved; otherwise, both cannot be achieved at the same time. A NDR technique yields more uniform effectiveness irrespective of the data, but it may not achieve as high data reduction as a well-suited PDR technique.
Popular NDR techniques include histograms, clustering and indexes. Histograms are used to approximate data distributions. An equidepth...
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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. Q. Bull. IEEE TC on Data Engineering, 20(4):3–45, 1997.
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Zhang, R. (2009). Nonparametric Data Reduction Techniques. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_546
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DOI: https://doi.org/10.1007/978-0-387-39940-9_546
Publisher Name: Springer, Boston, MA
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