PCA — Principal Component Analysis

About this app

Principal axes of a 3D point cloud as eigenvectors of the covariance: projection onto k components with perpendiculars, reconstruction error = sum of the discarded λ, scree plot, standardising and the difference from the regression plane.

Subject: Machine Learning

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