Model

A model is a parameterized function or system that maps inputs to outputs. After training and evaluation, it can capture patterns and make predictions or decisions on new, real-world inputs.

In machine learning, “model” may refer to the architecture, the learned parameters, or both. The architecture sets structure and capacity, while parameters are learned during training.

Model behavior reflects the interplay of data, the training process, and inductive biases. Performance is measured with task-appropriate metrics such as accuracy, precision, recall, F1 score, or mean Average Precision (mAP).