Overfitting happens when sample characteristics are included in the regression model that can be generalized to new data.

Question

Quizplus · Accepted Answer

Overfitting occurs when a model learns the detail and noise in the training data to the extent that it negatively impacts the performance of the model on new data. This means the model is too complex, capturing noise or random fluctuations in the training data as if they were important patterns, which do not generalize well to unseen data.

Overfitting Happens When Sample Characteristics Are Included in the Regression