Title :
Feature Selection in Pattern Recognition
Author :
Fu, K.S. ; Min, Pyung June ; Li, Timothy J.
Author_Institution :
Department of Electrical Engineering, Purdue University, Lafayette, Ind.
Abstract :
The problem of feature selection in pattern recognition is briefly reviewed. Feature selection techniques discussed include 1) information theoretic approach, 2) direct estimation of error probability, 3) feature-space transformation, and 4) approach of using stochastic automata model. These techniques are applied to the selection of features in the crop classification problem. Computer similation results are presented and compared.
Keywords :
Automata; Covariance matrix; Crops; Density functional theory; Entropy; Error probability; Estimation error; Pattern recognition; Size measurement; Stochastic processes;
Journal_Title :
Systems Science and Cybernetics, IEEE Transactions on
DOI :
10.1109/TSSC.1970.300326
