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Principal component analysis (PCA) is often used for analyzing data in themost diverse areas. In this work, we report an integrated approach to severaltheoretical and practical aspects of PCA. We start by providing, in anintuitive and accessible manner, the basic principles underlying PCA and itsapplications. Next, we present a systematic, though no exclusive, survey ofsome representative works illustrating the potential of PCA applications to awide range of areas. An experimental investigation of the ability of PCA forvariance explanation and dimensionality reduction is also developed, whichconfirms the efficacy of PCA and also shows that standardizing or not theoriginal data can have important effects on the obtained results. Overall, webelieve the several covered issues can assist researchers from the most diverseareas in using and interpreting PCA.

Principal Component Analysis: A Natural Approach to Data Exploration