What term describes a value that is passed as an input to a model?

The term that describes a value passed as an input to a model is "feature." In the context of machine learning, features are the individual measurable properties or characteristics of the data being analyzed. Each feature is an input that the model uses to make predictions or classifications. For example, if you're developing a model to predict house prices, the features could include the number of bedrooms, square footage, and location—each being a distinct piece of information used by the model.

Understanding features is crucial because they have a significant impact on the performance of the model. The quality and relevance of the features can influence the model's accuracy and efficiency, making feature engineering a vital step in the machine learning process.