This tutorial, based on a published book by Giovanni Seni, offers a hands-on intro to ensemble models, which combine multiple models into a single predictive system that’s often more accurate than the best of its components. Participants will use data sets and snippets of R code to experiment with the methods to gain a practical understanding of this breakthrough technology.
Giovanni Seni is currently a Senior Data Scientist with Intuit where he leads the Applied Data Sciences team. As an active data mining practitioner in Silicon Valley, he has over 15 years R&D experience in statistical pattern recognition and data mining applications. He has been a member of the technical staff at large technology companies, and a contributor at smaller organizations. He holds five US patents and has published over twenty conference and journal articles. His book with John Elder, “Ensemble Methods in Data Mining – Improving accuracy through combining predictions”, was published in February 2010 by Morgan & Claypool. Giovanni is also an adjunct faculty at the Computer Engineering Department of Santa Clara University, where he teaches an Introduction to Pattern Recognition and Data Mining class.
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