In machine learning, what does "training data" refer to?

Training data refers to the specific dataset used to train a machine learning model. During the training process, the model learns from this data by identifying patterns, making adjustments, and improving its performance in making predictions or decisions based on new, unseen data. Training data typically consists of input-output pairs, where the input data contains features, and the output is the target value that the model is trying to predict.

This phase is crucial as the quality and quantity of the training data directly impact the model's accuracy, generalization, and overall effectiveness. The model uses training data to optimize its parameters and minimize error, effectively learning how to map input to output before it can be evaluated on new unseen data.