Recognition of Exon/Intron Boundaries Using Dynamic Ensembles
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Attribute Clustering for Grouping, Selection, and Classification of Gene Expression Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Predicting the product purchase patterns of corporate customers
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Recommendation method for extending subscription periods
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A probabilistic classifier system and its application in data mining
Evolutionary Computation
On the structural properties of massive telecom call graphs: findings and implications
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Computer assisted customer churn management: State-of-the-art and future trends
Computers and Operations Research
Spectral clustering in telephone call graphs
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Social ties and their relevance to churn in mobile telecom networks
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Expert Systems with Applications: An International Journal
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
Customer churn prediction using improved balanced random forests
Expert Systems with Applications: An International Journal
An improved approach to find membership functions and multiple minimum supports in fuzzy data mining
Expert Systems with Applications: An International Journal
Privacy preserving churn prediction
Proceedings of the 2009 ACM symposium on Applied Computing
Spectral Clustering in Social Networks
Advances in Web Mining and Web Usage Analysis
Optimization of a training set for more robust face detection
Pattern Recognition
A Modular Distributed Decision Support System with Data Mining Capabilities
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Customer Churn Prediction for Broadband Internet Services
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Classification rule discovery with DE/QDE algorithm
Expert Systems with Applications: An International Journal
Adaptive genetic programming for dynamic classification problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A novel two level evolutionary approach for classification rules extraction
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Data Mining Using Rules Extracted from SVM: An Application to Churn Prediction in Bank Credit Cards
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Mining gene expression patterns for the discovery of overlapping clusters
EvoBIO'08 Proceedings of the 6th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Study on customer churn prediction methods based on multiple classifiers combination
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
In-depth behavior understanding and use: The behavior informatics approach
Information Sciences: an International Journal
Application of data mining techniques for customer lifetime value parameters: a review
International Journal of Business Information Systems
Pattern discovery for large mixed-mode database
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
An extended support vector machine forecasting framework for customer churn in e-commerce
Expert Systems with Applications: An International Journal
Building comprehensible customer churn prediction models with advanced rule induction techniques
Expert Systems with Applications: An International Journal
Local PCA regression for missing data estimation in telecommunication dataset
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Customer churn prediction --a case study in retail banking
Proceedings of the 2010 conference on Data Mining for Business Applications
IEEE Transactions on Evolutionary Computation
A granular agent evolutionary algorithm for classification
Applied Soft Computing
Using genetic K-means algorithm for PCA regression data in customer churn prediction
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Using PCA to predict customer churn in telecommunication dataset
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction
Expert Systems with Applications: An International Journal
A rule-based method for customer churn prediction in telecommunication services
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Customer churn prediction in telecommunications
Expert Systems with Applications: An International Journal
An intelligent customer retention system
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Predicting customer churn through interpersonal influence
Knowledge-Based Systems
User modeling for telecommunication applications: experiences and practical implications
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Expert Systems with Applications: An International Journal
Computers and Electrical Engineering
High-Performance Computing for Data Analytics
DS-RT '12 Proceedings of the 2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications
Churn management optimization with controllable marketing variables and associated management costs
Expert Systems with Applications: An International Journal
Predicting group evolution in the social network
SocInfo'12 Proceedings of the 4th international conference on Social Informatics
Different approaches to community evolution prediction in blogosphere
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Customer attrition in retailing: An application of Multivariate Adaptive Regression Splines
Expert Systems with Applications: An International Journal
Mobile phone customer retention strategies and Chinese e-commerce
Electronic Commerce Research and Applications
International Journal of Interdisciplinary Telecommunications and Networking
Profit optimizing customer churn prediction with Bayesian network classifiers
Intelligent Data Analysis - Business Analytics and Intelligent Optimization
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Classification is an important topic in data mining research. Given a set of data records, each of which belongs to one of a number of predefined classes, the classification problem is concerned with the discovery of classification rules that can allow records with unknown class membership to be correctly classified. Many algorithms have been developed to mine large data sets for classification models and they have been shown to be very effective. However, when it comes to determining the likelihood of each classification made, many of them are not designed with such purpose in mind. For this, they are not readily applicable to such problems as churn prediction. For such an application, the goal is not only to predict whether or not a subscriber would switch from one carrier to another, it is also important that the likelihood of the subscriber's doing so be predicted. The reason for this is that a carrier can then choose to provide a special personalized offer and services to those subscribers who are predicted with higher likelihood to churn. Given its importance, we propose a new data mining algorithm, called data mining by evolutionary learning (DMEL), to handle classification problems of which the accuracy of each predictions made has to be estimated. In performing its tasks, DMEL searches through the possible rule space using an evolutionary approach that has the following characteristics: 1) the evolutionary process begins with the generation of an initial set of first-order rules (i.e., rules with one conjunct/condition) using a probabilistic induction technique and based on these rules, rules of higher order (two or more conjuncts) are obtained iteratively; 2) when identifying interesting rules, an objective interestingness measure is used; 3) the fitness of a chromosome is defined in terms of the probability that the attribute values of a record can be correctly determined using the rules it encodes; and 4) the likelihood of predictions (or classifications) made are estimated so that subscribers can be ranked according to their likelihood to churn. Experiments with different data sets showed that DMEL is able to effectively discover interesting classification rules. In particular, it is able to predict churn accurately under- different churn rates when applied to real telecom subscriber data.