model testing

Model testing refers to the process of evaluating a predictive model to ensure it accurately captures relationships in data and performs well on new, unseen information. In general knowledge contexts, this involves using specific tests to check the model's effectiveness, including how well it predicts outcomes and how reliably it represents real-world scenarios. By analyzing its performance through metrics like accuracy or error rates, developers can identify strengths and weaknesses, leading to improvements. Ultimately, model testing is essential for building confidence in the decisions derived from the model's predictions.