The Data Science Lab Anomaly Detection Using Principal Component Analysis (PCA) The main advantage of using PCA for anomaly detection, compared to alternative techniques such as a neural autoencoder, ...

Using the two principal components of a point cloud for robotic grasping as an example, we will derive a numerical implementation of the PCA, which will help to understand what PCA is and what it does ...

This course will cover statistical approaches to dimension reduction using principal components and factor analysis, and classification using discriminant functions. The first part will outline the ...

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 ...