论文信息 - A nonlinear distance metric criterion for feature selection in the measurement space

A nonlinear distance metric criterion for feature selection in the measurement space

Abstract In this paper a nonlinear distance metric criterion for feature selection in the measurement space is proposed. The criterion is not only a more reliable measure of class separability than criteria based on the Euclidean distance metric but also computationally more efficient.

Josef Kittler

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