Post-Conference Data Mining Workshop
Wednesday, March 19
1:30 - 5:00 p.m.
This post-conference, one-half day workshop on data mining offers even more opportunity to expand your SAS data mining and predictive modeling skills. Stay later to take advantage of exclusive training opportunities. This workshop is designed for marketers, data analysts, business analysts and executives who want to understand the best practices of conducting end-to-end analytics – from data preparation to exploratory analysis to predictive modeling and implementation. This workshop introduces and demonstrates the introductory and advanced features available in the SAS® Enterprise MinerTM and SAS® Text MinerTM. Experience with either product is not required to attend. The $140 fee includes a box lunch.
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Market Segmentation Using the Tools in SAS® Enterprise MinerTM
Goutam Chakraborty, PhD, Professor, Oklahoma State University
This session covers segmentation analysis in the context of business data mining. The session provides a quick overview of theory of segmentation as well as the main analytic tools for building segments and validating segments in SAS Enterprise Miner: K-means clustering, SOM/Kohonen and segment profiler. Participants will get a sense of how to use each of these techniques in creating and profiling segments of customers so that these segments can be differentially targeted for marketing promotions/communications. The presentation will include several demonstrations using SAS Enterprise Miner and business data sets.
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Introduction to SAS® Enterprise MinerTM
Tom Bohannon, President, Analytical Business Solutions
Predictive modelers and data miners face many challenges when performing analyses. SAS Enterprise Miner software offers a graphical platform to streamline that analytical process. From exploratory tools like a flexible graphics interface to sophisticated modeling algorithms, SAS Enterprise Miner has much to offer. This presentation will demonstrate the use of SAS Enterprise Miner for creating a binary target response model. We will start with a SAS data set that contains information about responders and non-responders and mimic a typical modeling process. The end result will be SAS code that can be used to apply the best model to new data.
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How to Turn Text into Knowledge: An Introduction to SAS® Text Miner TM
Pat Cerrito, Professor, University of Louisville
This presentation will provide the basics of using SAS Text Miner to find information on the Web or to examine a collection of documents contained within a Windows directory. SAS Text Miner, a node in SAS Enterprise Miner, can use the links to a keyword search to find related documents. Then the algorithms provided in SAS Text Miner can use the sentence structure in the documents to cluster documents that are related. SAS Text Miner can also be used to analyze open-ended survey questions as well as calls into a customer support center. Using an example, we will demonstrate the text mining process, starting with the documents and ending with a use in subsequent statistical analyses. Other potential applications of SAS Text Miner will also be discussed.