A statistical technique for evaluating the significance of control parameters of mapping procedures

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Abstract

In this article, a strategy for estimating the significance of control parameters of mapping procedures is suggested. It is based on cross-classification analysis using measures of association. The proposed strategy provides a method for the objective estimation of the significance of control parameters, as opposed to the estimation by experience that is typically used. In a companion paper an application of the proposed method for evaluating the significance of the control parameters of a nonparametric linear mapping procedure is described. It demonstrates the effectiveness of the method.

Original languageEnglish
Pages (from-to)631-636
Number of pages6
JournalPattern Recognition Letters
Volume14
Issue number8
DOIs
StatePublished - 1 Jan 1993

Keywords

  • Mapping of multidimensional data
  • classifier design
  • feature extraction
  • measures of association

ASJC Scopus subject areas

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

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