Pca, Principal Components, Dimensionality Reduction, Eigenvectors, Eigenvalue.
variables is 0.99 which becomes 0 in the principal components. In raw data, variance in X1 and X2 was 8.67 and 27.33 respectively, with 24%-76%. In the principal components, most of the variance is captured in PC1 which is 99.9% Hence, we can clearly see the advantages of using principal components