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 ...

Dimension Reduction and Classification Using PCA, Factor Analysis and Discriminant Functions - A Short Overview Course Topics Tuesday, October 28: Often researchers are faced with data in very high ...