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Mathematics

Principal Component Analysis for Dimension Reduction

Quick fact

PCA was invented in 1901 by Karl Pearson, but it only became widely used after computers made the calculations practical.

Why this is interesting

Imagine you have a dataset with hundreds of measurements for each item, but you suspect only a few underlying trends matter. How can you simplify it without losing the essence?