Principal Component Analysis (PCA)

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Principal Component Analysis (PCA)

PCA is a statistical technique introduced by mathematician Karl Pearson in 1901. It works by transforming high-dimensional data into a lower-dimensional space while maximizing the variance (or spread) of the data in the new space. This helps preserve the most important patterns and relationships in the data.

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https://www.geeksforgeeks.org/principal-component-analysis-pca/