CompTIA
DY0-001 · Question #9
Which of the following describes the appropriate use case for PCA?
The correct answer is A. Dimensionality reduction. Principal Component Analysis transforms correlated features into a smaller set of uncorrelated components that capture most of the variance, making it ideal for reducing dimensionality before modeling or visualization.
Machine Learning
Question
Which of the following describes the appropriate use case for PCA?
Options
- ADimensionality reduction
- BClassification
- CRegression
- DRecommendation
How the community answered
(28 responses)- A86% (24)
- B4% (1)
- C4% (1)
- D7% (2)
Explanation
Principal Component Analysis transforms correlated features into a smaller set of uncorrelated components that capture most of the variance, making it ideal for reducing dimensionality before modeling or visualization.
Topics
#PCA#dimensionality reduction#unsupervised learning#feature reduction
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