A mathematical function that is used to measure the difference or error between a predicted value and the actual or observed value. In machine learning, a loss function is typically used to train models and optimize their parameters by minimizing the difference between predicted and actual values.
The loss function quantifies the error between the predicted output of a model and the actual output. It takes as input the predicted output of the model and the actual output, and returns a scalar value that represents the error. The objective of the model is to minimize this error, which is done by adjusting the model’s parameters during the training process.