A linear regression model is able to predict the output accurately for a given set of inputs. What underlying factor is primarily responsible for the model's performance in terms of prediction accuracy?

The model’s structure, which is defined by how its parameters are arranged, decides what patterns it can capture. Other options are incorrect because People often think the loss function is the main reason for accuracy, but it only tells the optimizer how to adjust parameters; It is a common mistake to believe that more parameters automatically improve accuracy.