Eigenvectors, Data Science, Analytics, Principal Component, Graph.
to get more accurate results and avoid curse of dimentionality. In such scenarios, PCA is used to reduce number of dimensions and conduct statistical analysis (there are other methods like factor analyser and LDA) Typical steps involved in PCA is as follows: Standardization of continuous variables