Identify Cross-Selling Opportunities via Hybrid Classifier

Identify Cross-Selling Opportunities via Hybrid Classifier

Dahong Qiu (Huazhong University of Science and Technology, China), Ye Wang (Huazhong University of Science and Technology, China) and Bin Bi (Huazhong University of Science and Technology, China)
Copyright: © 2008 |Pages: 8
DOI: 10.4018/jdwm.2008040107
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Abstract

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.

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