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Data Reduction 2: Numerosity Reduction

  • Reduce data volume by choosing alternative, smaller forms of data representation
  • Parametric methods (e.g., regression)
    • Assume the data fits some model, estimate model parameters, store only the parameters, and discard the data (except possible outliers)
    • Ex.: Log-linear models—obtain value at a point in m-D space as the product on appropriate marginal subspaces
  • Non-parametric methods
    • Do not assume models
    • Major families: histograms, clustering, sampling, …

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