Certified Tester AI Testing
Domain 3Objective 6
Factors Involved in ML Algorithm Selection CT-AI Practice Questions (Page 5)
Part of the Domain 3: Machine Learning (ML) - Overview domain, which makes up ~15% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~4–6 in this domain), expect 1–1 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)
29questions here
6free pages
8concepts
Questions 21–25
- 21
A medical diagnostics company is developing a model to detect a rare disease from lab results. The disease occurs in only 2% of the population. The cost of a false negative is extremely high (missing a disease), while false positives lead to additional tests. The model must be interpretable for doctors. Which metric should be the primary guide for algorithm selection?
Select an answer first - 22
A single decision tree has high variance, and its predictions change significantly with small changes in the training data. Which approach is most suitable to address this?
Select an answer first - 23
What is the typical trade-off when choosing between a simple linear model and a complex ensemble model?
Select an answer first - 24
A social media company wants to classify user posts as toxic or non-toxic. The text data is high-dimensional (bag-of-words with 50,000 features) and sparse. They have a large dataset of 1 million posts. The model needs to be trained on a single machine with limited memory. Which algorithm is most suitable?
Select an answer first - 25
How does algorithm complexity generally relate to the risk of overfitting?
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