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Abstract:
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How would you like to use data mining in addition to classical statistical modeling? In this presentation, specifically 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 that you will be able to build your own data mining models on your own datasets. Data mining is a powerful extension to classical statistical analysis. As opposed to classical techniques, data mining easily finds patterns in data, non-linear 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).
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