Improving feature extraction by replacing the Fisher criterion by an upper error bound
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Date
2005-07-07T12:28:03Z
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Abstract
A lot of alternatives and constraints have been proposed in order to improve the Fisher criterion. But most of them are not linked to the error rate, the primary interest in many applications of classification. By introducing an upper bound for the error rate a criterion is developed which can improve the classification performance.
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Keywords
Error bound, Feature extraction, Fisher criterion, Linear discriminant analysis