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Basic Question 4 of 8
Which one is NOT a hyperparameter?
B. The number of clusters in which to partition the data in K-means clustering
C. The number of principal components to retain in PCA
A. The number of nearest neighbors in K-nearest neighbor
B. The number of clusters in which to partition the data in K-means clustering
C. The number of principal components to retain in PCA
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I am using your study notes and I know of at least 5 other friends of mine who used it and passed the exam last Dec. Keep up your great work!
Barnes
Learning Outcome Statements
describe unsupervised machine learning algorithms - including principal components analysis, k-means clustering, and hierarchical clustering - and determine the problems for which they are best suited;
CFA® 2025 Level II Curriculum, Volume 1, Module 6.