Principal Component Analysis

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