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Monday, June 27 • 10:30am - 12:00pm
Never Tell Me the Odds! Machine Learning with Class Imbalances (Part 2)

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This tutorial will provide an overview of using R to create effective predictive models in cases where at least one class has a low event frequency. These types of problems are often found in applications such as: click through rate prediction, disease prediction, chemical quantitative structure - activity modeling, network intrusion detection, and quantitative marketing. The session will step through the process of building, optimizing, testing, and comparing models that are focused on prediction. A case study is used to illustrate functionality.

For details, refer to tutorial description.

avatar for Max "topepo" Kuhn

Max "topepo" Kuhn

Software Engineer, former scientist, RStudio
As chosen by my CAH deck, I am: | | - Leveling up | - Being knowledgable in a narrow domain that nobody understands or cares about | - Jean-Claude Van Damme in slow motion | - Giving 110% | - The Hamburgler | - A time travel paradox | - Sunshine and rainb... Read More →

Monday June 27, 2016 10:30am - 12:00pm
Econ 140 579 Serra Mall, Stanford, CA 94305

Attendees (63)