Machine Learning Fundamentals › Overfitting & Underfitting
What are common mistakes to avoid with Overfitting & Underfitting
IntermediateAnswer
A common mistake is making a model more and more complex to chase higher training accuracy, which usually makes overfitting worse instead of helping the real performance.
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.