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Estimating Local Dimensionality

Published

Author(s)

D L. Banks, R Olszewski

Abstract

This paper suggests that one can use principal components analysis to assess the local dimensionality in a complex dataset. If this is large, then data mining is unlikely to be successful. If it is small, then various statistical techniques may be able to uncover hidden structure.
Citation
American Statistical Association Section on Computational Statistics

Keywords

curse of dimensionality, data mining, nonparametrics

Citation

Banks, D. and Olszewski, R. (1997), Estimating Local Dimensionality, American Statistical Association Section on Computational Statistics, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=151731 (Accessed June 19, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created December 15, 1997, Updated February 17, 2017