What term is used to describe the set of data used to train an algorithm or model?

The term that describes the set of data used to train an algorithm or model is "training data." This data is crucial because it serves as the primary source of information from which the algorithm learns to make predictions or decisions. The training data provides examples that allow the algorithm to identify patterns, relationships, and underlying structures within the dataset, which it can later apply to new, unseen data.

In the context of machine learning and data science, training data is distinct from other types of datasets, like validation sets or test sets, which are used for evaluating the model's performance after it has been trained. The emphasis on training data highlights its role as the foundational input for the learning process, enabling algorithms to improve their accuracy and effectiveness when applied in real-world scenarios.