TITLE: Finding the Gold in Your Data: an Overview of Data Mining Techniques

TITLE: Finding the Gold in Your Data: an Overview of Data Mining Techniques

<p>TITLE: Finding the Gold in your Data: An Overview of Data Mining Techniques Room: National Harbour 12 8:00 – 11:30 a.m. Presenter: Dave Dickey (William Neal Reynolds Distinguished Professor of Statistics, NC State University) Course Description: (Intermediate)</p><p>This course consists of an introduction to the main techniques in data mining. It is structured around paper 501-2013 from the 2013 SASTM Global Forum and provides deeper insights into the main components of Enterprise Miner. It includes demos of the basic techniques available in this data mining tool. Main topics include decision trees, regression trees, neural networks, logistic regression, association analysis, text mining, and clustering. Rather than a detailed mathematical approach, this is an introductory overview of the tools available with examples to illustrate the concepts. </p><p>The course is at an intermediate level statistically only in that familiarity with basic statistical ideas will help in interpreting and appreciating the results that will be shown. In terms of SAS it is at an elementary level. It does not require SAS programming knowledge beyond a very elementary level and in fact should be accessible even to those with little or no programming experience. It is meant as an introductory overview tour of the SAS Enterprise Miner suite of analytics.</p><p>TM SAS is the registered trademark of SAS Institute, Cary, NC</p><p>Need Bio</p><p>Professor David Dickey received his PhD from Iowa State University under Wayne Fuller. The resulting “Dickey Fuller test” is available in most time series software packages including SAS PROC ARIMA. Google Scholar shows 100 published papers with about 29,500 citations for him in the scientific literature. Dave teaches data mining both in NCSU’s Institute for Advanced Analytics and its Statistics Department, is a books by users author, a SAS Contract Instructor, a Fellow of the American Statistical Association, and a frequent speaker at SAS Global Forum and regional users’ groups. He holds a named Distinguished Professor Chair at NCSU and has advised 16 PhD students as well as being co- chairman for several others. He is also an associate member of the Department of Agricultural and Resource Economics.</p><p>TM SAS is the registered trademark of SAS Institute, Cary, NC</p><p>1</p>

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