mathematical optimization, loss functions for classification are computationally feasible loss functions representing the price paid for inaccuracy of predictions...

symmetric, differentials cases. Bayesian regret Loss functions for classification Discounted maximum loss Hinge loss Scoring rule Statistical risk Hastie, Trevor;...

than the squared error loss. A variant for classification is also sometimes used. The Huber loss function describes the penalty incurred by an estimation...

Muthiah-Nakarajan, Venkataraman (March 17, 2023). "Alternate loss functions for classification and robust regression can improve the accuracy of artificial...

the hinge loss is a loss function used for training classifiers. The hinge loss is used for "maximum-margin" classification, most notably for support vector...

{\displaystyle {\hat {f}}(x)={\text{Median}}(y|X=x)} . Proof: The Loss functions for classification is L = E [ | y − a | | X = x ] = ∫ − ∞ ∞ | y − a | f Y | X...

for the loss function to be convex. Different loss functions are used depending on whether the problem is one of regression or one of classification....

distributions are predicted. Scoring rules and scoring functions are often used as "cost functions" or "loss functions" of probabilistic forecasting models. They...

activation functions at layer l {\displaystyle l} For classification the last layer is usually the logistic function for binary classification, and softmax...

Connectionist temporal classification (CTC) is a type of neural network output and associated scoring function, for training recurrent neural networks...