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Principal Component Analysis (PCA)

Principal Component Analysis (PCA) finds new orthogonal axes (principal components) that capture the maximum variance in your data.

#principal component analysis#pca c++#eigendecomposition+11
∑MathIntermediate

Eigendecomposition

Eigendecomposition expresses a matrix as a change of basis times a diagonal scaling, revealing its natural stretching directions.

#eigendecomposition
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+11
📚TheoryIntermediate

Singular Value Decomposition (SVD)

Singular Value Decomposition (SVD) factors any m×n matrix A into A = UΣV^{T}, where U and V are orthogonal and Σ is diagonal with nonnegative entries.

#singular value decomposition#svd#truncated svd+12