Principal component analysis

Principal Component Analysis (PCA) is a statistical method used to reduce the dimensionality of data while preserving its variance. By transforming data into a new coordinate system, PCA identifies the directions (principal components) along which the data varies the most. The first principal component accounts for the largest variance, the second for the next largest, and so on. This allows for ___ ______ ______ __________ ____.
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