DM1: Introduction: Machine Learning and Data Mining - Sorry

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<strong>Data</strong> <strong>Mining</strong> for Customer Modeling • Customer Tasks: • attrition prediction • targeted marketing: • cross-sell, customer acquisition • credit-risk • fraud detection • Industries • banking, telecom, retail sales, … 14
Customer Attrition: Case Study •Situation: Attrition rate at for mobile phone customers is around 25-30% a year! •With this in mind, what is our task? • Assume we have customer information for the past N months. 15
Page 1 and 2: Machine Learning, Data Mining, and
Page 3 and 4: Lesson Outline •Introduction: Dat
Page 5 and 6: Big Data Examples • Europe's Very
Page 7 and 8: From terabytes to exabytes to …
Page 9 and 10: Data Growth In 2 years, the size of
Page 13: Application Areas What do you think
Page 17 and 18: Customer Attrition Results • Veri
Page 19 and 20: Credit Risk - Results • Banks dev
Page 21 and 22: Successful e-commerce - Case Study
Page 23 and 24: Genomic Microarrays - Case Study Gi
Page 25 and 26: Security and Fraud Detection - Case
Page 29 and 30: Related Fields Machine Learning Vis
Page 31 and 32: Knowledge Discovery Process flow, a
Page 35 and 36: Data Mining Tasks: Classification L
Page 37 and 38: Summary: • Technology trends lead
Page 39: 1997 1998 1999 2000 2001 2002 2003

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