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Data Reduction Process

Data reduction techniques can be applied to obtain a reduced representation of the data set that ismuch smaller in volume, yet closely maintains the integrity of the original data.

Data reduction strategies include dimensionality reduction, numerosity reduction, and data compression.

Dimensionality reduction is the process of reducing the number of random variables or attributes under consideration.

Dimensionality Reduction Methods

  • Wavelet Transforms
  • Principal Components Analysis
  • Attribute Subset Selection

Numerosity reduction techniques replace the original data volume by alternative, smaller forms of data representation.

Numerosity Reduction Methods

  • Parametric
    •  Regression
    •  Log Linear
  • Non Parametric
    •  Histogram
    •  Clustering
    •  Sampling
    •  Data cube aggregation

In data compression techniques, transformations are applied so as to obtain a reduced or compressed representation of the original data.

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