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Identify Cross-Selling Opportunities via Hybrid Classifier:
| Our Price: |
$30.00 US |
| Article #: |
ITJ4203 |
| Number of pages: |
55-62 pages |
| Source: |
International Journal of Data Warehousing and Mining, Vol. 4, Issue 2 |
| Author(s): |
Qiu, Dahong; Wang, Ye; Bi, Bin |
| Affiliation(s): |
Huazhong University of Science and Technology, China; Huazhong University of Science and Technology, China; Huazhong University of Science and Technology, China |
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Description
This article presents our solution to PAKDD’07 Data Mining Competition, whose task is to build a classifier to score the propensity of a credit card customer to take up a home loan with a finance company. After analyzing the task, we first describe the data preparation steps in detail. Then, a mixed resampling method is put forward to deal with the problem that model samples are redundant and class imbalance. Following that, a hybrid classifier that integrates Logistic Regression, Adaboost with Decision Stump and Voting Feature Intervals, is built. It is evaluated via cross-identification. Finally, some useful business insights gained from our solution are interpreted. |
