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Principal_Component_Analysis_PCA

Principal component analysis in rstudio is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. The data is linearly transformed onto a new coordinate system such that the directions capturing the largest variation in the data can be easily identified.

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Principal component analysis in rstudio is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. The data is linearly transformed onto a new coordinate system such that the directions capturing the largest variation in the data can be easily identified.

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