Surrogate Loss Functions and Fisher Consistency in Binary Classification
An in-depth exploration of surrogate loss functions, their convexity properties, and Fisher consistency in binary classification, explaining the theory behind popular losses like hinge, exponential, logistic, and truncated quadratic.
