JSM 2012 Online Program
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Online Program HomeActivity Details
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| CE_30T | Wed, 8/1/2012, 8:00 AM - 9:45 PM | HQ-Indigo 206 | |
| Advances in Data Mining, State-of-the-Art Algorithms from Jerome Friedman: GPS (Generalized Pathseeker), ISLE (Importance Sampled Learning Ensembles), and RULEFIT Rule Extraction Engine — Continuing Education CTW | |||
| ASA , Salford Systems | |||
| Instructor(s): Mikhail Golovnya, Salford Systems | |||
| Using real world data sets we will demonstrate Stanford Professor Jerome Friedman's advances in regularized linear and logistic regression and important extensions to gradient boosted tree technology. GPS: Allows for ultra-fast modeling with massive numbers of predictors, with powerful predictor selection and coefficient shrinkage, includes classic techniques such as ridge and lasso regression, and also the new sub-lasso model, and clear tradeoff diagrams between model complexity and predictive accuracy allow modelers to select an ideal balance. ISLE: for the compression of tree ensembles and complex many-tree ensembles can be simplified and pruned via ISLE compression yielding simpler and faster executing ensembles. RULEFIT: using TreeNet and/or RandomForests tree ensembles as rule search engines, RULEFIT extracts individual nodes to exhibit interesting and predictive rules, rules are optimally combined to yield models that are often more accurate than the original ensembles, and RULEFIT supports individual specific and group specific variable importance rankings and offers dependency plots for model interpretation This tutorial will show real world examples, discuss key algorithmic details, and cover implementation and best practices. All attendees will receive 6 months access to fully functional versions of the software. Prerequisites: This course is intended to be accessible to anyone with experience with regression modeling. | |||
2012 JSM Online Program Home
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