What term describes the use of a previously trained model to predict outcomes based on new data?

The term that describes the use of a previously trained model to predict outcomes based on new data is "Prediction." This process involves leveraging insights and patterns learned during the training phase of the model on historical data and applying that knowledge to make forecasts or decisions about unseen data.

Prediction is a fundamental aspect of machine learning, where the model's effectiveness is evaluated based on its ability to generalize its findings to new, unobserved inputs. This can occur in various domains, such as finance, healthcare, and marketing, among others, where accurate predictions can lead to improved decision-making and strategic planning.

The concept emphasizes the importance of using available data to inform future outcomes, making it a key focus in cognitive project management for AI applications. In contrast, the other terms are related concepts but do not specifically capture the essence of using a model to anticipate future results based on unseen data.