In the context of toxicology, cross-validation is a statistical method used to estimate the skill of a machine learning model. It involves partitioning a dataset into complementary subsets, training the model on one subset, and validating it on the other. This process is repeated multiple times to ensure the results are robust and not dependent on a particular train-test split.
