Title :
On the Discriminant Vector Method of Feature Selection
Author_Institution :
Department of Electronics, University of Southampton
fDate :
6/1/1977 12:00:00 AM
Abstract :
The correspondence discusses the relationship of the discriminant vector method of feature selection [1] and the method of Kittler and Young [5]. Although both methods determine the feature space coordinate axes by maximizing the generalized Fisher criterion of discriminatory power, with the exception of two class case the resulting feature spaces are considerably different because of the difference in the constraints imposed on the axes by individual methods. It is shown that the latter method is, from the point of view of dimensionality reduction, more powerful and also computationally more efficient.
Keywords :
Dimensionality reduction, feature selection, information compression, Karhunen–expansion, pattern recognition.; Decision making; Optimization methods; Pattern recognition; Scattering; Dimensionality reduction, feature selection, information compression, Karhunen–expansion, pattern recognition.;
Journal_Title :
Computers, IEEE Transactions on
DOI :
10.1109/TC.1977.1674885