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Principal component analysis(PCA)MLAI/DimensionalityReduction 2019. 10. 5. 17:32
1. Overview Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. This transformation is defined in such a way that the first principal compo..