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Unformatted text preview: Statistical Data Mining ORIE 4740 Prof. Dawn Woodard Cornell University 1 Outline 1 Motivation / Examples 2 Course summary 3 Overview of Learning and Prediction 4 Review of Background Concepts 2 Business Applications Market segmentation Finding groups of customers with similar purchasing habits Evaluating risk of credit card applicants Targeted marketing Identifying likely purchasers Home valuation 4 Aircraft Identification Predicting the type of aircraft based on its location at a series of time points. 5 Identification of Cancer Genes Finding genes that show very high or low expression in individuals with a particular cancer 6 Information Tech. Applications Search engine technology Identifying spam Handwriting and voice recognition Smart web browsers that identify ads on web pages 7 Data mining “Data mining is the application of [statistical and machine learning] techniques to common business problems” - Two Crows Intro. Finding hidden, meaningful, and often unsuspected information in data Data mining often involves large data sets with many records (e.g. customers) and many variables (attributes). Desirable approaches are both meaningful and computationally tractable on these large data sets....
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This note was uploaded on 12/23/2009 for the course ORIE 4740 at Cornell.