Probability, Calibration, Machine Learning, Data Science, Model Tuning.
cross-entropy loss, evaluates the accuracy of probabilistic predictions made by a model. It quantifies the difference between the predicted probabilities and the actual outcomes, considering the entire probability distribution. A lower Log-loss value indicates better calibration, with the ideal