Welcome to the InfoSci Platform
Reference Hub5
Identify Cross-Selling Opportunities via Hybrid Classifier

Identify Cross-Selling Opportunities via Hybrid Classifier

Dahong Qiu, Ye Wang, Bin Bi
Copyright: © 2008 |Volume: 4 |Issue: 2 |Pages: 8
ISSN: 1548-3924|EISSN: 1548-3932|ISSN: 1548-3924|EISBN13: 9781615202041|EISSN: 1548-3924|DOI: 10.4018/jdwm.2008040107
Cite Article Cite Article

MLA

Qiu, Dahong, et al. "Identify Cross-Selling Opportunities via Hybrid Classifier." IJDWM vol.4, no.2 2008: pp.55-62. http://doi.org/10.4018/jdwm.2008040107

APA

Qiu, D., Wang, Y., & Bi, B. (2008). Identify Cross-Selling Opportunities via Hybrid Classifier. International Journal of Data Warehousing and Mining (IJDWM), 4(2), 55-62. http://doi.org/10.4018/jdwm.2008040107

Chicago

Qiu, Dahong, Ye Wang, and Bin Bi. "Identify Cross-Selling Opportunities via Hybrid Classifier," International Journal of Data Warehousing and Mining (IJDWM) 4, no.2: 55-62. http://doi.org/10.4018/jdwm.2008040107

Export Reference

Mendeley
Favorite Full-Issue Download

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.