What Is Loss function?
In machine learning, the loss function is a measure of how well a model fits the training data. It is a function that is minimized during training.
The loss function is typically a mathematical function that measures the difference between the predicted values and the actual values. It is used to train the model by minimizing the loss function.
The loss function is used to train the model, while the test set is used to evaluate the performance of the model. The test set is typically a random sample of the dataset that is not used to train the model.