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Basic Question 0 of 10
In a K-nearest neighbor model, choosing a value for k that is too small would result in ______.
B. overfitting
C. underfitting
A. high error rate
B. overfitting
C. underfitting
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I am happy to say that I passed! Your study notes certainly helped prepare me for what was the most difficult exam I had ever taken.
Andrea Schildbach
Learning Outcome Statements
describe supervised machine learning algorithms - including penalized regression, support vector machine, k-nearest neighbor, classification and regression tree, ensemble learning, and random forest - and determine the problems for which they are best suited;
CFA® 2025 Level II Curriculum, Volume 1, Module 6.