Combination of multiple classifiers for the customer's purchase behavior prediction

Authors:
Eunju Kim;Wooju Kim;Yillbyung Lee
Affiliations:
Department of Computer Science, Yonsei University, 134, Shinchon-dong, Seodaemoon-ku, Seoul 120-749, South Korea;Department of Industrial Engineering, Chonbuk National University, 664-14 Deokjin, Chonju, Chonbuk 561-756, South Korea;Department of Computer Science, Yonsei University, 134, Shinchon-dong, Seodaemoon-ku, Seoul 120-749, South Korea
Venue:
Decision Support Systems - Special issue: Agents and e-commerce business models
Year:
2003

Citing 8
Cited 29

Learning internal representations by error propagation

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Handwritten numerical recognition based on multiple algorithms

Pattern Recognition
Decision Combination in Multiple Classifier Systems

IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining Your Website

Data Mining Your Website
Machine Learning

Machine Learning
Combining Classifiers

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Integrating fuzzy knowledge by genetic algorithms

IEEE Transactions on Evolutionary Computation
Multiple network fusion using fuzzy logic

IEEE Transactions on Neural Networks

Enterprise integration using the agent paradigm: foundations of multi-agent-based integrative business information systems

Decision Support Systems
Web-based intervention support system for health promotion

Decision Support Systems
Incorporating sequential information into traditional classification models by using an element/position-sensitive SAM

Decision Support Systems
Metadata and its impact on libraries: Book Reviews

Journal of the American Society for Information Science and Technology
Applying knowledge engineering techniques to customer analysis in the service industry

Advanced Engineering Informatics
Context-based market basket analysis in a multiple-store environment

Decision Support Systems
Listed companies' financial distress prediction based on weighted majority voting combination of multiple classifiers

Expert Systems with Applications: An International Journal
Electronic promotion to new customers using mkNN learning

Information Sciences: an International Journal
A supply-chain-oriented business process reengineering strategy for on-demand new product development

International Journal of Computer Applications in Technology
Boosting and measuring the performance of ensembles for a successful database marketing

Expert Systems with Applications: An International Journal
Review: Application of data mining techniques in customer relationship management: A literature review and classification

Expert Systems with Applications: An International Journal
A decision support system for detecting products missing from the shelf based on heuristic rules

Decision Support Systems
Financial distress prediction based on serial combination of multiple classifiers

Expert Systems with Applications: An International Journal
Combination of multiple classifiers for post-placement quality inspection of components: A comparative study

Information Fusion
Application architecture of data mining in telecom customer relationship management based on swarm intelligence

PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Pattern classification driven enhancements for human-in-the-loop decision support systems

Decision Support Systems
Predicting stock returns by classifier ensembles

Applied Soft Computing
AdaBoost ensemble for financial distress prediction: An empirical comparison with data from Chinese listed companies

Expert Systems with Applications: An International Journal
Estimating the effect of word of mouth on churn and cross-buying in the mobile phone market with Markov logic networks

Decision Support Systems
Aggregating multiple classification results using Choquet integral for financial distress early warning

Expert Systems with Applications: An International Journal
Dynamic classifier ensemble model for customer classification with imbalanced class distribution

Expert Systems with Applications: An International Journal
The prediction for listed companies' financial distress by using multiple prediction methods with rough set and Dempster-Shafer evidence theory

Knowledge-Based Systems
Forecasting medical cost inflation rates: A model comparison approach

Decision Support Systems
Serial combination of multiple classifiers for automatic blue whale calls recognition

Expert Systems with Applications: An International Journal
Financial distress prediction using support vector machines: Ensemble vs. individual

Applied Soft Computing
Distributed customer behavior prediction using multiplex data: A collaborative MK-SVM approach

Knowledge-Based Systems
Mining actionable behavioral rules

Decision Support Systems
An efficient tree-based algorithm for mining sequential patterns with multiple minimum supports

Journal of Systems and Software
A cellular learning automata model of investment behavior in the stock market

Neurocomputing

Quantified Score

Hi-index	0.01

Visualization

Abstract

In these days, EC companies are eager to learn about their customers using data mining technologies. But the diverse situations of such companies make it difficult to know which is the most effective algorithm for the given problems. Recently, a movement towards combining multiple classifiers has emerged to improve classification results. In this paper, we propose a method for the prediction of the EC customer's purchase behavior by combining multiple classifiers based on genetic algorithm. The method was tested and evaluated using Web data from a leading EC company. We also tested the validity of our approach in general classification problems using handwritten numerals. In both cases, our method shows better performance than individual classifiers and other known combining methods we tried.