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# Principal component analysis

The previous methods we have examined are supervised - they are used to predict some `\(y\)` outcome variable based on `\(x\)` predictors. Principal component analysis (PCA) is an unsupervised method, which does not use any `\(y\)` variable for supervision but instead sorts the data based _only_ on the `\(x\)` variables. PCA and other ordination/dimension reduction techniques are helpful for optimizing other machine learning algorithms. 

PCA is a powerful linear tran