Explain Principal Component Analysis (PCA)?
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Answer / Veeresh Kumar Shakya
Principal Component Analysis (PCA) is a technique used in data analysis to reduce the dimensionality of data while retaining most of its important features.nIt works by finding the principal components, or directions of maximum variance in the data, and projecting the data onto these new axes. This can make the data easier to visualize and analyze without losing too much information.
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