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Principal Component Analysis (PCA)

Principal component analysis is a statistical technique of factor analysis and dimensionality reduction that transforms a set of possibly correlated initial features into a smaller set of linearly uncorrelated features called principal components. In this way, PCA preserves as much variance in the dataset as possible, while minimizing the number of features.

Principal Component Analysis (PCA)

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