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Numerical Classification

  • Paul Switzer
Chapter
Part of the Computer Applications in the Earth Sciences book series

Abstract

The first section briefly reviews the rationales and some shortcomings of commonly used techniques for sorting samples into homogeneous classes. The second section suggests that computer screening of large numbers of differently oriented data projections may provide useful insights into configuration of the samples.

Keywords

Random Projection Sample Profile Numerical Classification Trial Projection Current Screening Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Ball, G. H., and Hall, D. J., 1970, Some implications of interactive graphic computer systems for data analysis and statistics: Technometrics, v. 12, p. 17–31.Google Scholar
  2. Day, N. E., 1969, Estimating the components of a mixture of normal distributions: Biometrika, v. 56, p. 463–475.Google Scholar
  3. Demirmen, F., 1969, Multivariate procedures and FORTRAN IV program for evaluation and improvement of classifications: Kansas Geol. Survey Computer Contr. 31, 51 p.Google Scholar
  4. Engleman, L., and Hartigan, J. A., 1969, Percentage points of a test for clusters: Jour. Am. Stat. Assoc., v. 64, p. 1647–1648.CrossRefGoogle Scholar
  5. Fortier, J. J., and Solomon, H., 1966, Clustering procedures, in Multivariate analysis: Academic Press, New York, p. 493–506.Google Scholar
  6. Friedman, H. P., and Rubin, J., 1967, On some invariant criteria for grouping data: Jour. Am. Stat. Assoc., v. 62, p. 1159–1178.CrossRefGoogle Scholar
  7. Gower, J. C., 1970, Classification and geology: Review Intern. Stat. Inst., v. 38, p. 35–41.CrossRefGoogle Scholar
  8. Johnson, S. C., 1967, Hierarchical clustering schemes: Psychometrika, v. 32, p. 241–254.Google Scholar
  9. King, B., 1967, Stepwise clustering procedures: Jour. Am. Stat. Assoc., v. 62, p. 79–85.CrossRefGoogle Scholar
  10. MacQueen, J., 1965, Some methods for classification and analysis of multivariate observations: 5th Berkeley Sym. on Probability and Statistics, p. 281–297.Google Scholar
  11. Sokal, R. R., and Sneath, P. H. A., 1963, Principles of numerical taxonomy: W. H. Freeman and Co., San Francisco, 359 p.Google Scholar
  12. Wilks, S. S., 1960, Multidimensional statistical scatter, in Contributions to probability and statistics in honor of H. Hotelling: Stanford Univ. Press, p. 486–503.Google Scholar

Copyright information

© Plenum Press, New York 1970

Authors and Affiliations

  • Paul Switzer
    • 1
  1. 1.Stanford UniversityUSA

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