Video available at: http://www.youtube.com/watch?v=MFilAoiV5nE
Decision trees are a widely used machine learning technique for supervised classification. Indeed's data sets consist of tens of billions of documents with millions of distinct features. Since decision trees back some of our most important features, we built a custom distributed system to efficiently train them. Every day, we now build dozens of decision trees across this data. This same system now powers our internal analytical tools that enable quick data-driven decision-making at Indeed.
This presentation provides a brief introduction to decision trees followed by a detailed overview of our approach to building them. The talk will be presented by our CTO, Andrew Hudson.