Principal Component Analysis (PCA) is a technique for exploratory data analysis with many success applications in several research fields. It is often used in image processing, data analysis, data pre-processing, visualization and is often used as one of the most basic building steps in many complex algorithms.
One of the most popular resources for learning about PCA is the excellent tutorial due to Lindsay I Smith. On her tutorial, Lindsay gives an example application for PCA, presenting and discussing the steps involved in the analysis.
Souza, C. R. "A Tutorial on Principal Component Analysis with the Accord.NET Framework". Department of Computing, Federal University of São Carlos, Technical Report, 2012. |
This said, the above technical report aims to show, discuss and otherwise present the reader to the Principal Component Analysis while also reproducing all Lindsay's example calculations using the Accord.NET Framework. The report comes with complete source C# code listings and also has a companion Visual Studio solution file containing all sample source codes ready to be tinkered inside a debug application.
While the text leaves out the more detailed discussions about the exposed concepts to Lindsay and does not addresses them in full details, it presents some practical examples to reproduce most of the calculations given by Lindsay on her tutorial using solely Accord.NET.
If you like a practical example on how to perform matrix operations in C#, this tutorial may help getting you started.