Principal Component Analysis (PCA) Basic algorithm Raw process data usually includes several variables correlating with each other and increasing the dimensionality of the system or disturbing the regression analysis. Principal Component Analysis, PCA, is a conventional method to decrease this dimensionality without losing the information in the correlated variables. It searches for fewer linear combinations
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