CAF-3 · Chapter 10 · Question 7 of 15
Which dimensionality reduction technique is used to reduce the number of features in a massive dataset while preserving as much variance as possible, making it easier to analyze?
Test yourself: pick an answer
Reveal answer & explanation
Correct answer: A) Principal Component Analysis (PC
Explanation
PCA is an unsupervised dimensionality reduction technique used to simplify large datasets while preserving their most critical information (variance)
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