Parametric and nonparametric linear mappings of multidimensional data

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Abstract

A new criterion for linear mapping of the samples from two classes is presented. Some parametric and nonparametric forms of the criterion are suggested. Based on them most of the known linear mapping projections can be created. New projections can be obtained as well. An experimental study with synthetic and real data is discussed. It confirms the effectiveness of the new mapping projections for the data with complicated classification structure.

Original languageEnglish
Pages (from-to)543-553
Number of pages11
JournalPattern Recognition
Volume24
Issue number6
DOIs
StatePublished - 1 Jan 1991

Keywords

  • Classifier design
  • Exploratory data analysis
  • Feature extraction
  • Mapping

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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