Explanation:
PCA is an unsupervised learning approach for reducing dimensionality (i.e., it is not concerned with forecasting a target value). On the other hand, partial least squares (PLS) is an example of supervised dimension reduction.
(Book 2, Module 25.2, LO 25.e)
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Principal component analysis (PCA) is a popular dimension reduction method. Which of the following machine learning categories is associated with PCA?
A
Supervised learning.
B
Unsupervised learning.
C
Reinforcement learning.
D
Semi-supervised learning.
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