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 language | English |
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Pages (from-to) | 631-636 |
Number of pages | 6 |
Journal | Pattern Recognition Letters |
Volume | 14 |
Issue number | 8 |
DOIs | |
State | Published - 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