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What is Geometric Interpretation of PCA about?
This document provides a geometric explanation of principal component analysis (PCA) in three dimensions. It explains that PCA involves finding the best-fit line through multidimensional data that captures the maximum variance. This best-fit line defines the first principal component. The second principal component is the line perpendicular to the first that captures the second greatest variance. Together, the principal components define a plane or hyperplane that best approximates the original multidimensi
- Author
- Deepak Padiyar
- Language
- EN