Machine Learning - Special issue on learning with probabilistic representations
Estimating campaign benefits and modeling lift
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Solving regression problems with rule-based ensemble classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Neural, Novel and Hybrid Algorithms for Time Series Prediction
Neural, Novel and Hybrid Algorithms for Time Series Prediction
Mastering Data Mining: The Art and Science of Customer Relationship Management
Mastering Data Mining: The Art and Science of Customer Relationship Management
Machine Learning
Incorporating Prior Knowledge into Boosting
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Comparison of Classification Methods for Customer Attrition Analysis
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Semi-parametric optimization for missing data imputation
Applied Intelligence
Temporal rule induction for clinical outcome analysis
International Journal of Business Intelligence and Data Mining
Predicting credit card customer churn in banks using data mining
International Journal of Data Analysis Techniques and Strategies
Expert Systems with Applications: An International Journal
Behavioral assessment of recoverable credit of retailer's customers
Information Sciences: an International Journal
Business intelligence for delinquency risk management via cox regression
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction
Expert Systems with Applications: An International Journal
A new neural network based customer profiling methodology for churn prediction
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part IV
DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique
Applied Intelligence
Improving customer retention in financial services using kinship network information
Expert Systems with Applications: An International Journal
A service oriented architecture to provide data mining services for non-expert data miners
Decision Support Systems
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Deregulation within the financial service industries and the widespread acceptance of new technologies is increasing competition in the finance marketplace. Central to the business strategy of every financial service company is the ability to retain existing customers and reach new prospective customers. Data mining is adopted to play an important role in these efforts. In this paper, we present a data mining approach for analyzing retailing bank customer attrition. We discuss the challenging issues such as highly skewed data, time series data unrolling, leaker field detection etc, and the procedure of a data mining project for the attrition analysis for retailing bank customers. We use lift as a proper measure for attrition analysis and compare the lift of data mining models of decision tree, boosted naïve Bayesian network, selective Bayesian network, neural network and the ensemble of classifiers of the above methods. Some interesting findings are reported. Our research work demonstrates the effectiveness and efficiency of data mining in attrition analysis for retailing bank.