juniorModel Evaluation
What is overfitting in model evaluation?
Updated May 17, 2026
Short answer
Overfitting occurs when a model learns training data too well, including noise.
Deep explanation
An overfit model performs well on training data but poorly on unseen data due to excessive complexity or memorization.
Real-world example
A stock prediction model that performs perfectly on historical data but fails in live trading.
Common mistakes
- Using overly complex models without regularization.
Follow-up questions
- How to prevent overfitting?
- How to detect it?