Legend: Boston Convention & Exhibition Center = CC, Westin Boston Waterfront = W, Seaport Boston Hotel = S
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
Activity Details
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| CE_35T | Wed, 8/6/2014, 1:00 PM - 2:45 AM | W-Douglass | |
| Evolution of Classification: From Logistic Regression and Decision Trees to Bagging/Boosting and Netlift Modeling: Case Study Examples Drawn from Direct Marketing and Biomedical Data Analysis — 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. For example, previously we targeted all the people who are likely to buy (or respond to a clinical treatment), and included segments that we now can accurately exclude: for example, 1. those who would've purchased even without treatment 2. those who would be less likely to buy if treated. 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. This workshop will be of value to any classically trained statistician or modeler. The workshop will be especially interesting to those looking to better understand the newest advances in segmenting their databases and detecting subsets of populations. This will be especially of interest to direct marketers and biomedical researchers. Keywords: netlift, uplift, data mining, analytics, direct marketing, biostatistics, Random Forests, TreeNet, Stochastic Gradient Boosting, data mining, logistic regression, regularized logistic regression, decision trees, bagging, boosting, incremental modeling, true lift modeling. All attendees will receive 6 months access to fully functional versions of the SPM Salford Predictive Modeler software suite. Prerequisites: None | |||
| Instructor(s): Mikhail Golovnya, Salford Systems | |||
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