loss function

During training or testing, a mathematical function that calculates the loss on a batch of examples. A loss function returns a lower loss for models that makes good predictions than for models that make bad predictions. The goal of training is typically to minimize the loss that a loss function returns. Many different kinds of loss functions exist. Pick the appropriate loss function for the kind of model you are building. For example: - L2 loss (or Mean Squared Error) is the loss function for linear regression. - Log Loss is the loss function for logistic regression.

Practitioners refer to loss function when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.