feed-forward neural networks is the recommended loss function for binary classification this loss function should typically be used when the neural network is designed to predict the probability of the outcome in such casesthe output layer has single unit with suitable sigmoid as the activation function the cross-entropy function given by the expression yi log xi is the recommended loss function for multiclassification this loss function should typically be used with the neural network designed to predict the probability of the outcomes of each of the classes in such casesthe output layer has softmax units (one for each class the squared loss function given by = should be used for regression problems the output layer in this case will have single unit several other loss functions could be used for classification and regressioncovering the exhaustive list would be beyond the scope of the few notable loss functions are huber loss (regressionand hinge loss (classification