A loss function in machine learning is a mathematical function used to quantify the difference between the predicted values and the actual values. This function plays a crucial role in training models by guiding the optimization process to minimize the error, ultimately improving the model's predictions. In the context of cancer research, loss functions are particularly significant for model development in areas such as diagnosis, prognosis, and treatment planning.
