Anomaly Detection Using Principal Component Analysis (PCA)

added by DotNetKicks
10/21/2021 3:39:24 PM

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Principal component analysis (PCA) is a classical statistics technique that breaks down a data matrix into vectors called principal components. The principal components can be used for several different purposes. One way to use PCA components is to examine a set of data items to find anomalous items using reconstruction error.


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