The main advantage of using PCA for anomaly detection, compared to alternative techniques such as a neural autoencoder, is simplicity -- assuming you have a function that computes eigenvalues and ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

Matteo Mazziotta, Adriano Pareto, Use and Misuse of PCA for Measuring Well-Being, Social Indicators Research, Vol. 142, No. 2 (April 2019), pp. 451-476 ...