In machine learning, what term is used for the dataset used to train a model?

In machine learning, the dataset used to train a model is referred to as training data. This data serves as the foundational input from which the model learns to make predictions or classifications. By utilizing training data, the model identifies patterns, relationships, and features important for its predictions based on the provided examples.

Training data is distinct from other types of datasets used in the model evaluation process. Evaluation data is typically used to assess the performance of the model in a simulated real-world scenario. Validation data acts as a check during the model training process to tune hyperparameters and avoid overfitting, while testing data is reserved for final evaluation after the model has been trained. Each of these other datasets plays a crucial role in a comprehensive machine learning workflow, but training data is specifically designated for the initial learning phase of the model.