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Modeling the Telemarketing Process Using Genetic Algorithms and Extreme Boosting: Feature Selection and Cost-Sensitive Analytical Approach
14 references·0 citing·50 second hop
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References

  • 2002Sensitivity Analysis for Importance Assessment1,303 cited
  • 2014A data-driven approach to predict the success of bank telemarketing875 cited
  • 2022Extending the resource and knowledge based view: Insights from new contexts of analysis164 cited
  • 2020Missing Data Preprocessing in Credit Classification: One-Hot Encoding or Imputation?155 cited
  • 2018Mutual information and sensitivity analysis for feature selection in customer targeting: A comparative study55 cited
  • 2022Towards Explainable Machine Learning for Bank Churn Prediction Using Data Balancing and Ensemble-Based Methods53 cited
  • 2020Business Analytics in Telemarketing: Cost-Sensitive Analysis of Bank Campaigns Using Artificial Neural Networks51 cited
  • 2021A dynamic ensemble selection method for bank telemarketing sales prediction42 cited
  • 2021Credit Scoring Models Using Ensemble Learning and Classification Approaches: A Comprehensive Survey38 cited
  • 2020Cost-sensitive ensemble methods for bankruptcy prediction in a highly imbalanced data distribution: a real case from the Spanish market36 cited
  • 2017A divide‐and‐conquer strategy using feature relevance and expert knowledge for enhancing a data mining approach to bank telemarketing28 cited
  • 2022How to improve the success of bank telemarketing? Prediction and interpretability analysis based on machine learning18 cited
  • 2021Improving the Accuracy of Predicting Bank Depositor’s Behavior Using a Decision Tree

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16 cited
  • 2021Comparative Study of Machine Learning Algorithms for Portuguese Bank Data12 cited
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