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- W54616674 abstract "This report describes our participation in Knowledge Discovery and Data Mining (KDD) 2009 cup compe-tition . The competition is a set of three separate binary classification problems, based on a large marketingdatabase of Orange Telecom. The problems are churn, appetency and upselling. We tried variations of threealternate techniques to tackle the problem - Naive bayesian , Decision Trees and Support Vector Machines.Section 2 describes the problems posed in further detail and Section 3 gives the evaluation criteria. In Sec-tion 4 we discuss the three approaches and the variations and Section 5 provides a discussion on the results.We propose future directions for our work in Section 6." @default.
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- W54616674 date "2009-01-01" @default.
- W54616674 modified "2023-09-23" @default.
- W54616674 title "Classification of Churn,Upselling and Appetency for KDD Cup 2009" @default.
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