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  • This article compares the performance of parametric and nonparametric discrimination. After a brief description of the discriminant analysis problem the parametric and nonparametric approaches are described. The multivariate product Gaussian and polynomial kernels with various datadriven choices of the bandwidth are used for density estimators and this nonparametric approaches are compared with classical one by some real data. Overall percentages of the misclassification and computer time are used as the measure of performance.
  • This article compares the performance of parametric and nonparametric discrimination. After a brief description of the discriminant analysis problem the parametric and nonparametric approaches are described. The multivariate product Gaussian and polynomial kernels with various datadriven choices of the bandwidth are used for density estimators and this nonparametric approaches are compared with classical one by some real data. Overall percentages of the misclassification and computer time are used as the measure of performance. (en)
  • This article compares the performance of parametric and nonparametric discrimination. After a brief description of the discriminant analysis problem the parametric and nonparametric approaches are described. The multivariate product Gaussian and polynomial kernels with various datadriven choices of the bandwidth are used for density estimators and this nonparametric approaches are compared with classical one by some real data. Overall percentages of the misclassification and computer time are used as the measure of performance. (cs)
Title
  • A Comparison of Some Parametric and Nonparametric Discrimination Procedures
  • A Comparison of Some Parametric and Nonparametric Discrimination Procedures (en)
  • A Comparison of Some Parametric and Nonparametric Discrimination Procedures (cs)
skos:prefLabel
  • A Comparison of Some Parametric and Nonparametric Discrimination Procedures
  • A Comparison of Some Parametric and Nonparametric Discrimination Procedures (en)
  • A Comparison of Some Parametric and Nonparametric Discrimination Procedures (cs)
skos:notation
  • RIV/00216224:14310/02:00007723!RIV08-MSM-14310___
http://linked.open.../vavai/riv/strany
  • 53-81
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  • Z(MSM 143100001)
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  • 636954
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  • RIV/00216224:14310/02:00007723
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  • linear and quadratic discriminant analysis; nonparametric discriminant analysis; kernel density estimation; product kernels; bandwidth choice (en)
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  • [99122A7731DD]
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  • Brno
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  • Brno
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  • Summer School DATASTAT 01 Folia Facultatis Scientiarum Naturalium Universitatis Masarykianae Brunensis
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  • Forbelská, Marie
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Folia Facultatis Scientiarum Naturalium Universitatis Masarykianae Brunensis, Mathematica
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  • 80-210-3028-3
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  • 14310
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