The Library of Congress > Linked Data Service > LC Subject Headings (LCSH)

Dimension reduction (Statistics)


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  • Variants

    • Dimensionality reduction (Statistics)
    • Reduction, Dimension (Statistics)
    • Reduction, Dimensionality (Statistics)
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  • Closely Matching Concepts from Other Schemes

  • Sources

    • found: Work cat.: Thangavelu, M. On error bounds for linear feature extraction, 2010.
    • found: Wikipedia, accessed, Jan. 11, 2010(Redirected from Dimensionality reduction) For dimensional reduction in physics, see Dimensional reduction. Dimension reduction - In statistics, dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature extraction. Feature selection approaches try to find a subset of the original variables (also called features or attributes). Two strategies are filter (e.g. information gain) and wrapper (e.g. genetic algorithm) approaches. Feature extraction is applying a mapping of the multidimensional space into a space of fewer dimensions. This means that the original feature space is transformed by applying e.g. a linear transformation via a principal components analysis.)
    • found: Zhy, M. Feature extraction and dimension reduction with applications to classification and the analysis of co-occurrence data, 2001.
    • found: Fargues, M. Investigation of feature dimension reduction schemes for classification applications, 2001.
    • found: Wang, Q. Sufficient dimension reduction and sufficient variable selection, 2009.
    • notfound: McGraw-Hill dictionary of scientific and technical terms, 2003
  • Change Notes

    • 2010-01-11: new
    • 2010-02-20: revised
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