datamining-intro-IEP (1).ppt

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  An Introduction to Data Mining Prof. S. SudarshanCSE Dept, IIT BombayMost slides courtesy:Prof. Sunita SarawagiSchool of IT, IIT Bombay  Why Data Mining  Credit ratings/targeted marketing :  Given a database of 100,000 names, which persons are the least likely to default on their credit cards?  Identify likely responders to sales promotions  Fraud detection  Which types of transactions are likely to be fraudulent, given the demographics and transactional history of a particular customer?  Customer relationship management :  Which of my customers are likely to be the most loyal, and which are most likely to leave for a competitor? : Data Mining helps extract such information  Data mining  Process of semi-automatically analyzing large databases to find patterns that are:  valid: hold on new data with some certainity  novel: non-obvious to the system  useful: should be possible to act on the item  understandable: humans should be able to interpret the pattern   Also known as Knowledge Discovery in Databases (KDD)  Applications  Banking: loan/credit card approval  predict good customers based on old customers  Customer relationship management:  identify those who are likely to leave for a competitor.  Targeted marketing:  identify likely responders to promotions  Fraud detection: telecommunications, financial transactions  from an online stream of event identify fraudulent events  Manufacturing and production:  automatically adjust knobs when process parameter changes
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