The two most common techniques for dimensionality reduction are using PCA (principal component analysis) and using a neural autoencoder ... into a 200-item set to be reduced and a 40-item set to act ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...