Principal Component Analysis (PCA) Feature Selection

The definition of principal component analysis (PCA) from wikipedia is: a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.

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