15062_Spring_2008

15062_Spring_2008 - Spring 2008 (Welsch) Data Mining:...

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Spring 2008 (Welsch) Data Mining: Finding the Data and Models that Create Value 15.062 Information Sheet Summary and Goals: Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the Internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, microarrays, genomic sequences, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. A number of successful applications have been reported in areas such as credit rating, fraud detection, database marketing, customer relationship management, stock market investments, and bioinformatics. The field of data mining has evolved from the disciplines of statistics (multivariate analysis) and artificial intelligence (machine learning). This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective. We will survey applications and provide an opportunity for hands-on experimentation with algorithms for data mining with easy-to-use software and cases. Our objective is to develop an understanding of the strengths and limitations of popular data mining techniques and to be able to identify promising business applications of data mining. Students will be able to actively manage and participate in data mining projects that have been converted into cases. A useful takeaway from the course will be the ability to perform powerful data analyses in Excel. Background: Material on statistics at the level of 15.060 (Data, Models, and Decisions) or 15.074 (Statistical Reasoning and Data Modeling) or 15.075 (Statistical Thinking and Data Analysis). Perhaps the most important topic is regression and you might want to review your notes. Instructor: Professor Roy Welsch, E53-383 (x3-6601), [email protected] Often, I am available after class, but the best way to see me is to schedule some time by email or phone. My office hours will be 4-5 on most Wednesdays (check first). Please also feel free to email me with your questions or comments. I will do my best to respond in a timely manner. We will use Stellar for
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This note was uploaded on 06/07/2011 for the course CS 512 taught by Professor Cube during the Spring '11 term at Central Texas College.

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15062_Spring_2008 - Spring 2008 (Welsch) Data Mining:...

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