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.
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Schedule a callMore From: IEEE Transactions on Systems Science and Cybernetics
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