Data Envelopment Analysis Tutorial

Data Envelopment Analysis, also known as DEA, is a non-parametric method for performing frontier analysis. It uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics. The technique was first proposed by Charnes, Cooper and Rhodes in 1978 and since then it became a valuable tool for estimating production frontiers. Update: The Datumbox Machine Learning Framework is now open-source and free to download. When I first encountered the method 5-6 years ago, I was amazed by the originality of the algorithm, its simplicity and the cleverness of the ideas that it used. I was even more amazed to see that the technique worked well outside of its usual applications (financial, operation research etc) since it could be successfully applied in Online Marketing, Search Engine Ranking and for creating composite metrics.