Uses For PCA Other Than Dimensionality Reduction Part 2¶

Imputation, and Noise Reduction¶

Principal Component Analysis (PCA) is frequently applied in machine learning as a sort of black box dimensionality reduction technique. However with a deeper understanding of what PCA is and what it does we can use it for all manner of other tasks e.g.

Asymptotic Labs (Posts about dimensionality reduction)

Imputing Missing Values With PCA

Uses For PCA Other Than Dimensionality Reduction Part 2¶

Imputation, and Noise Reduction¶