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This is the preliminary program for the 2006 Joint Statistical
Meetings in Seattle, Washington.
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The views expressed here are those of the individual authors and not necessarily those of the ASA or its board, officers, or staff. Back to main JSM 2006 Program page |
= Applied Session,
= Theme Session,
= Presenter, Sheraton Seattle Hotel & Towers = “S”| CE_05C | Sat, 8/5/06, 8:30 AM - 5:00 PM | CC-304 |
| Practical Data Mining - Continuing Education - Course | ||
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The ASA |
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| Instructor(s): Richard De Veaux, Williams College | ||
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This course will introduce data mining, the exploration and analysis of large datasets by automatic or semiautomatic means with the purpose of discovering meaningful patterns. The knowledge learned from theses patterns can be used for decisionmaking via a process known as "knowledge discovery." Much of exploratory data analysis and inferential statistics concern the same type of problems, so what is different about data mining? What is similar? We will attempt to answer these questions by providing a survey of the problems that motivate data mining and the approaches used to solve them. The course will be case-study and dataset-based and cover many of the algorithms used in data mining from an applications perspective. The applications will come from a variety of industries, and attendees will learn to identify appropriate problems for data mining, explore and prepare data for mining, apply two-stage models, use techniques such as decision trees and neural nets to build accurate predictive models, evaluate the quality of models, and select the appropriate data mining tools for applications. Course attendees are expected to be familiar with the topic at the level of: |
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JSM 2006
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. |