Applying the Decisiveness and Robustness Metrics to Convolutional Neural Networks

29 May 2020Christopher A. GeorgeEduardo A. BarreraKenric P. Nelson

We review three recently-proposed classifier quality metrics and consider their suitability for large-scale classification challenges such as applying convolutional neural networks to the 1000-class ImageNet dataset. These metrics, referred to as the "geometric accuracy," "decisiveness," and "robustness," are based on the generalized mean ($\rho$ equals 0, 1, and -2/3, respectively) of the classifier's self-reported and measured probabilities of correct classification... (read more)

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