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CFA Level II Vignettes Quantitative Finance Machine Learning MCQs Test 2
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CFA Level II Vignettes Quantitative Finance Machine Learning MCQs Test 2

Practice CFA 2026 Level II Vignettes Quantitative Finance MCQs from Machine Learning. Get instant results with Explanation.
Practice Quiz 2 for "Machine Learning" (Quantitative Finance). Total 30 MCQs available, split into 3 quizzes. Test your understanding of core concepts. Mastering these concepts is essential for securing a high percentile in CFA.
General10 MCQs
1. Vignette 3: Tree‑Based Methods - Which algorithm uses recursive binary splitting based on impurity measures like Gini index or entropy?
2. What ensemble method builds multiple models on bootstrapped samples and averages them to reduce variance?
3. Which ensemble method builds models sequentially, with each new model focusing on misclassified observations?
4. Which method is an ensemble of decision trees that uses both bootstrapped samples and random feature selection?
5. How is feature importance typically determined in a random forest?
General10 MCQs
6. Vignette 4: Unsupervised Learning – Clustering & PCA - Which algorithm assigns observations to clusters to minimize within‑cluster variance?
7. In K‑means clustering, what is the elbow method used for?
8. What is the primary purpose of Principal Component Analysis (PCA)?
9. What does the first principal component represent?
10. Which metric is used to evaluate the quality of clustering by measuring cohesion and separation?

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Frequency: 4 times a year (February, May, August, November) | Time: 70 Minutes
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