Actuarial Data Science

Bridging the Gap between Actuarial and Data Science

Fri 28 December 2018

PCA from several perspectives

Posted by Pieter Marres in Articles   

Principal Component Analysis (PCA) is a useful technique when you want to get a better understanding of a dataset containing a large number of correlated features. For example, in image processing, PCA is used for data compression. The main objective is to reduce the complexity of the data with a minimum loss of information.