Identify Cross-Selling Opportunities via Hybrid Classifier

Dahong Qiu; Ye Wang; Bin Bi

doi:10.4018/jdwm.2008040107

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Identify Cross-Selling Opportunities via Hybrid Classifier

Dahong Qiu, Ye Wang, Bin Bi

Source Title: International Journal of Data Warehousing and Mining (IJDWM) 4(2)

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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Identify Cross-Selling Opportunities via Hybrid Classifier

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