Machine Learning Fundamentals › Overfitting & Underfitting
How does Overfitting & Underfitting work
BeginnerAnswer
Overfitting is detected when training accuracy is high but testing accuracy is much lower. Underfitting is detected when both training and testing accuracy are low, meaning the model has not learned enough.
Real-world example A student who memorizes exact exam questions without understanding the topic is like an overfit model, while a student who barely studies at all is like an underfit model.