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Activity Details

CE_37T Wed, 8/2/2017, 1:00 PM - 2:45 PM H-Holiday Ballroom 3
Evolution of Classification: From Logistic Regression and Decision Trees to Bagging/Boosting and Netlift Modeling - Case Study Examples Drawn from Data Sets in Direct Marketing and Biomedical Data Analysis (ADDED FEE) — Professional Development Computer Technology Workshop
ASA , Salford Systems
Not so long ago, modelers would use traditional classification, data mining and decision tree techniques to identify a target population. We have come a long way in recent years. By incorporating modern approaches, including boosting, bagging and netlift, there has been a giant leap in this arena. This presentation will discuss recent improvements to conventional decision tree and logistic regression technology via two case study examples: one in Direct Marketing & the second drawn from Biomedical Data Analysis. Within the context of real-world examples, we will illustrate the evolution of classification by contrasting and comparing: Regularized Logistic Regression, CART, Random Forests, TreeNet Stochastic Gradient Boosting, and RuleLearner.
Instructor(s): Mikhail Golovnya, Salford Systems, Charles Harrison, Salford Systems, Dan Steinberg, Salford Systems
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