33_091111_CE16_DataMining

33_091111_CE16_DataMining - MIS 301 Introduction to IT...

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Unformatted text preview: MIS 301 Introduction to IT Management Lizhen Xu IROM Department McCombs School of Business Data Mining Ch Ex 16 Database Marketing Class Business Excel #3 Assignment Under BB->Assignments XL Miner, available in Millennium Lab Alone or with a partner Deadline Extended : Monday, Nov 16, beginning of class, Hard Copy Recap PB? EB? 4 types of BI systems? Reporting system; Data mining system; Knowledge management system; Expert system; Problems of operational data Wrong granularity : Too fine? Too coarse? Operational Database E Data Warehouse E Data Mart What is Data Mining? Definition : Non-trivial discovery of novel, valid, comprehensible and potentially useful patterns from data Pattern: relationship in data E.g., People with bad credit scores are more likely to have accidents. On Thursday nights, people who buy diapers also tend to buy beer Two categories: Unsupervised Supervised Unsupervised Data Mining Analysts do not create model before running analysis Apply data-mining technique and observe results Hypotheses created after analysis as explanation for results Example: cluster analysis Supervised Data Mining Model developed before analysis Statistical techniques used to estimate parameters Examples: Regression analysis Neural networks 1 2 3 4 1 class grade age major = + + + Data Mining Tasks Data mining commonly involves four classes of task : Clustering Classifications Regressions Association detection Clustering Cluster Analysis Similar records (or characteristics) are group together Does not rely on predefined categories ; being grouped together on...
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33_091111_CE16_DataMining - MIS 301 Introduction to IT...

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