Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A data scientist trains a regression model to predict house prices using features like bedrooms, square footage, and location. The model achieves a low error on the training data but performs significantly worse when used to predict prices in a new city with different property characteristics. Which concept best explains this poor performance?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Underfitting
Underfitting occurs when the model has high error on both training and test data, not just on new data.
B
Best answer
Overfitting
Overfitting means the model captures noise and specifics of the training data, leading to poor generalization to new data, especially from a different distribution.
C
Distractor review
Data leakage
Data leakage involves the model using information from outside the training set to make predictions, which is not indicated here.
D
Distractor review
Bias-variance tradeoff
While overfitting relates to high variance, the bias-variance tradeoff is a broader concept; overfitting is the most direct explanation for the described behavior.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
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FAQ
Questions learners often ask
What does this AI-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Overfitting — Overfitting occurs when a model learns the training data too well, including noise and specific patterns that do not generalize to new, unseen data. The model's poor performance on the new city indicates it failed to generalize beyond the original training distribution. Underfitting would show high error on both sets. Data leakage involves using future data, not relevant here. The bias-variance tradeoff is related but the specific failure is overfitting.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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