 Cross-entropy benchmarking

Cross-entropy benchmarking is a technique used to evaluate the performance of probabilistic models, particularly in the context of machine learning and statistical modeling. It involves measuring the effectiveness of a model in predicting a distribution of outcomes by comparing the predicted probability distribution to the true distribution of the data. ### Key Concepts: 1. **Cross-Entropy**: The cross-entropy is a measure of the difference between two probability distributions.