Gradient-based learning for F-measure and other performance metrics

Many important classification performance metrics, e.g. $F$-measure, are non-differentiable and non-decomposable, and are thus unfriendly to gradient descent algorithm. Consequently, despite their popularity as evaluation metrics, these metrics are rarely optimized as training objectives in neural network community... (read more)

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