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Mutual information and sensitivity analysis for feature selection in customer targeting: A comparative study
7 references·3 citing·46 second hop
Mutual information and sensitivity analysis for feature selection in customer targeting: A comparative study (2018)Mutual information and sensitivity analys…Beyond the hype: Big data concepts, methods, and analytics (2014)Beyond the hype: Big data con…A data-driven approach to predict the success of bank telemarketing (2014)A data-driven approach to pre…Data mining with big data (2013)Data mining with big dataDecision Support and Business Intelligence Systems (2006)Decision Support and Business…Customer relationship management: Finding value drivers (2006)Customer relationship managem…An intelligent system for customer targeting: a data mining approach (2003)An intelligent system for cus…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…A stacked ensemble learning method for customer lifetime value prediction (2023)A stacked ensemble learning m…Detecting the Risk of Customer Churn in Telecom Sector: A Comparative Study (2022)Detecting the Risk of Custome…Improving the Accuracy of Predicting Bank Depositor’s Behavior Using a Decision Tree (2021)Improving the Accuracy of Pre…Developing Buyer-Seller Relationships (1987)Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence (1988)The Commitment-Trust Theory of Relationship Marketing (1994)Customer relationship management and firm performance: the mediating role of business strategy (2009)Developing business customer engagement through social media engagement-platforms: An integrative S-D logic/RBV-informed model (2017)The effect of AI-based CRM on organization performance and competitive advantage: An empirical analysis in the B2B context (2021)Statistics for Experimenters (1979)Design and Analysis of Computer Experiments (1989)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Handbook on Constructing Composite Indicators (2005)An effective screening design for sensitivity analysis of large models (2007)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)The Value of Purchase History Data in Target Marketing (1996)Data mining for direct marketing: problems and solutions (1998)Mining the network value of customers (2001)Intelligent value-based customer segmentation method for campaign management: A case study of automobile retailer (2007)Evolving Least Squares Support Vector Machines for Stock Market Trend Mining (2008)Data Science Methodologies: Current Challenges and Future Approaches (2021)A framework for marketing management (2000)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)A Review on Fairness in Machine Learning (2022)The effects of data quality on machine learning performance on tabular data (2025)Big data: The next frontier for innovation, competition, and productivity (2011)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Data quality management, data usage experience and acquisition intention of big data analytics (2014)Critical analysis of Big Data challenges and analytical methods (2016)Machine learning on big data: Opportunities and challenges (2017)Setting the future of digital and social media marketing research: Perspectives and research propositions (2020)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Using data mining for bank direct marketing: an application of the CRISP-DM methodology (2011)Financial revolution: a systemic analysis of artificial intelligence and machine learning in the banking sector (2023)Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning (2024)Predictive Modeling of Customer Response to Marketing Campaigns (2024)A comparison of machine learning techniques for customer churn prediction (2015)Customer churn prediction in the telecommunication sector using a rough set approach (2016)Customer churn prediction in telecom using machine learning in big data platform (2019)Behavior Analysis Using Enhanced Fuzzy Clustering and Deep Learning (2022)Factors, Predictability, and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature (2024)Optimizing Customer Retention in the Telecom Industry: A Fuzzy-Based Churn Modeling with Usage Data (2024)Customer lifetime value: Marketing models and applications (1998)Modeling Customer Lifetime Value (2006)Beyond the ‘iron triangle’: Stakeholder perception of key performance indicators (KPIs) for large-scale public sector development projects (2009)Understanding Satisfied and Dissatisfied Hotel Customers: Text Mining of Online Hotel Reviews (2015)A survey on deep learning for big data (2017)Big Data technologies: A survey (2017)Machine Learning With Big Data: Challenges and Approaches (2017)
this work references cited by second hop

References

  • 2014Beyond the hype: Big data concepts, methods, and analytics4,222 cited
  • 2013Data mining with big data2,411 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 2014A data-driven approach to predict the success of bank telemarketing875 cited
  • 2006Decision Support and Business Intelligence Systems866 cited
  • 2006Customer relationship management: Finding value drivers407 cited
  • 2003An intelligent system for customer targeting: a data mining approach160 cited

Cited by

  • 2022Detecting the Risk of Customer Churn in Telecom Sector: A Comparative Study25 cited
  • 2021Improving the Accuracy of Predicting Bank Depositor’s Behavior Using a Decision Tree16 cited
  • 2023A stacked ensemble learning method for customer lifetime value prediction15 cited

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