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Basic Question 2 of 8
Which statement is false?
B. In PCA, composite variables can be easily labeled as they come directly from the initial data set.
C. In practice, retained principal components should be able to explain 85% to 95% of total variance in the initial data set.
A. In PCA, composite variables are uncorrelated.
B. In PCA, composite variables can be easily labeled as they come directly from the initial data set.
C. In practice, retained principal components should be able to explain 85% to 95% of total variance in the initial data set.
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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.