Abstract
Purchase PDF (479 K)
E-mail Article
Add to my Quick Links
Cited By in Scopus (1)
Purchase PDF (330 K)
doi:10.1016/0031-3203(79)90046-3 
Copyright © 1979 Published by Elsevier Science B.V.
Distance preserving linear feature selection
References and further reading may be available for this article. To view references and further reading you must purchase this article.
Received 21 March 1979;
Abstract
A new method for linear feature selection is described which has as its underlying theme the preservation of actual distances between training data points in the lower dimensional space. Comparison with existing methodology places the method closer to the principle components or Karhunen- Loève approach than to methods based on an approach through statistical pattern recognition. A computer program implementing the technique is described. An example application to 12 dimensional LANDSAT data is given.
Author Keywords: Linear feature selection; Principle components; Clustering; LANDSAT data
Article Outline
* Both authors were supported in part by NASA/Johnson Space Center, Contract NAS-9-14689, during the preparation of this work.
