Legend: Palais des congrès de Montréal = CC, Le Westin Montréal = W, Intercontinental Montréal = I
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_15C | Mon, 8/5/2013, 8:30 AM - 5:00 PM | W-Ville-Marie | |
| Successful Data Mining in Practice — Continuing Education Course | |||
| ASA , Section on Statistical Learning and Data Mining | |||
| Instructor(s): Richard D. De Veaux, Williams College | |||
| This one day course serves as a practical introduction to data mining. After an introduction to what data mining is, the types of problems it can solve and the challenges of data mining, we will use a sequence of case studies, mostly taken from my consulting experience, to illustrate the main methods and techniques used in data mining. Methods covered include decision trees, neural networks, naive Bayes, K-nearest neighbors, random forests, boosted trees and various visualization techniques. For each method we describe the mathematics behind it (without dwelling too much on technical details and all the optimization choices), and show how it is used in practice. We discuss how to choose methods for particular problems and how to evaluate the methods using cross validation. Unlike many courses in data mining, we spend a good deal of time talking about how to start a data mining project, the steps to follow and the issues in communicating results to others. We use R and JMP as software for the course (with a few examples in Weka). | |||
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
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