Legend: CC-W = McCormick Place Convention Center, West Building, CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago, UC= Conference Chicago at University Center
* = applied session ! = JSM meeting theme
Applied Data Mining Analysis: A Step-by-Step Introduction Using Real-World Data Sets (ADDED FEE) — Professional Development Computer Technology Workshop
ASA
How would you like to use data mining in addition to classical statistical modeling? In this presentation designed for statisticians, we will show how you can quickly and easily create data mining models. We will demonstrate with step-by-step instructions. We will use real-world data mining examples drawn from online advertising and the financial services industries. At the end of this workshop, our goal is for you to be able to build your own data-mining models on your own data sets. Data mining is a powerful extension to classical statistical analysis. As opposed to classical techniques, data mining easily finds patterns in data, nonlinear relationships, key predictors, and variable interactions that are difficult-if not impossible-to detect using standard approaches. This tutorial follows a step-step approach to introduce advanced automation technology-including CART, MARS, TreeNet Gradient Boosting, Random Forests, and the latest multi-tree boosting and bagging methodologies by the original creators of CART (Breiman, Friedman, Olshen, and Stone). All attendees will receive six months access to fully functional versions of the SPM Salford Predictive Modeler software suite.
Instructor(s): Mikhail Golovnya, Salford Systems, Dan Steinberg, Salford Systems
