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Parametric Data Reduction Techniques

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# Parametric Data Reduction Techniques

## Definition

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

Given a set of points (Assuming two dimensions.) {〈

((1)) |

*x*_{1},*y*_{1}〉, 〈*x*_{2},*y*_{2}〉,...}, parameters*a*and*b*in Equation