GATE DA 2026 Set 1 — Question 11
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Machine Learning → Dimensionality Reduction → Principal Component Analysis (PCA)
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Question
For a classification problem, Principal Component Analysis (PCA) has been used to reduce the dimensionality of a feature space from 100 to 10.
Which of the following options is true about the angle between the first and the tenth principal components?
Which of the following options is true about the angle between the first and the tenth principal components?
Correct answer
(B) θ = 90^
Solution
Principal Component Analysis (PCA) identifies a set of orthogonal axes (principal components) that capture the maximum variance in the data. By definition, all principal components are orthogonal (perpendicular) to each other. This means the dot product between any two distinct principal components is zero, and the angle between them is .Therefore, the angle between the first and the tenth principal components is .
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