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Ranking Potential Customers Based on Group-Ensemble:
| Our Price: |
$30.00 US |
| Article #: |
ITJ4205 |
| Number of pages: |
79-89 pages |
| Source: |
International Journal of Data Warehousing and Mining, Vol. 4, Issue 2 |
| Author(s): |
Zhang, Zhi-Zhuo; Chen, Qiong; Ke,Shang-Fu; Wu, Yi-Jun. Qi, Fei; Zhang, Ying-Peng |
| Affiliation(s): |
South China University of Technology, China; South China University of Technology, China; South China University of Technology, China; South China University of Technology, China; South China University of Technology, China; South China University of Technology, China |
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Description
Ranking potential customers has become an effective tool for company decision makers to design marketing strategies. The task of PAKDD competition 2007 is a cross-selling problem between credit card and home loan, which can also be treated as a ranking potential customers problem. This article proposes a 3-level ranking model, namely Group-Ensemble, to handle such kinds of problems. In our model, Bagging, RankBoost and Expending Regression Tree are applied to solve crucial data mining problems like data imbalance, missing value and time-variant distribution. The article verifies the model with data provided by PAKDD Competition 2007 and shows that Group-Ensemble can make selling strategy much more efficient. |
