Ctrl K
Sign inStart free
Data Scientist · Junior · Theory

What is model overfitting, and how do you detect it?

~4 min by voice

How to approach it

The interviewer checks whether the candidate understands overfitting as a model's poor ability to generalize, and can measure it honestly: splitting the data, comparing train/test metrics, cross-validation. A plus is knowing the causes, the remedies and related pitfalls such as underfitting and data leakage.

Have you seen this question in a real interview?
Answers0
Avg. score—
Strong—
Practiced0
Topics
machine learningoverfitting
Similar questionsYou trained a churn prediction model, the ROC AUC on validation is 0.97, but after deploying to production the quality is much worse. What causes would you check? Mid-levelA churn model showed a ROC-AUC of 0.93 on validation, but after it went into production, retention based on its recommendations didn't improve, and quality on fresh data is much lower. What causes would you check? Senior

Answer by voice

The interviewer will ask this question and listen. Think out loud and ask for a hint if you need one. When you're done, pause or tap “That's my answer”. In about a minute, your score and the points you covered show up here.

Sign in to answer

Best with headphones · ~4 min