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Churn prediction analysis of telecom customers using svm, random forest and logistic regression models using orange data mining tools
8 references·0 citing·41 second hop
Churn prediction analysis of telecom customers using svm, random forest and logistic regression models using orange data mining tools (2024)Churn prediction analysis of telecom cust…Integrated Churn Prediction and Customer Segmentation Framework for Telco Business (2021)Integrated Churn Prediction a…Customer Decision Prediction Using Deep Neural Network on Telco Customer Churn Data (2021)Customer Decision Prediction …Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking (2020)Evaluating Trust Prediction a…Churn Prediction in Telecommunication using Logistic Regression and Logit Boost (2020)Churn Prediction in Telecommu…Drivers for Pursuing Sustainability through IoT Technology within High-End Hotels—An Exploratory Study (2019)Drivers for Pursuing Sustaina…Churn modeling with probabilistic meta paths-based representation learning (2019)Churn modeling with probabili…Customer Churn Prediction Modelling Based on Behavioural Patterns Analysis using Deep Learning (2018)Customer Churn Prediction Mod…Telco Churn Prediction with Big Data (2015)Telco Churn Prediction with B…Applying data mining to telecom churn management (2005)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Handling class imbalance in customer churn prediction (2008)A Big Data Clustering Algorithm for Mitigating the Risk of Customer Churn (2016)Marketing analytics: Methods, practice, implementation, and links to other fields (2018)Leveraging unstructured call log data for customer churn prediction (2020)A Customer Churn Prediction Model in Telecom Industry Using Boosting (2012)Customer churn analysis in telecom industry (2015)A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic (2020)Deep Learning as a Vector Embedding Model for Customer Churn (2021)Intelligent Decision Forest Models for Customer Churn Prediction (2022)Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression (2007)Classifying the segmentation of customer value via RFM model and RS theory (2008)Social ties and their relevance to churn in mobile telecom networks (2008)A Counterfactual Modeling Framework for Churn Prediction (2022)Factors, Predictability, and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature (2024)A comprehensive survey on customer churn analysis studies (2025)Building Theories from Case Study Research (1989)Systematic combining: an abductive approach to case research (2002)Theory Building From Cases: Opportunities And Challenges (2007)Sustainability Efforts in the Hotel Industry: A Systematic Literature Review (2022)Building a Hierarchical Enablers Framework for Service Business Model Innovation for Sustainable Performance: Evidence from Ghana’s Electricity Sector (2024)Digital transformation and environmental sustainability in the hospitality industry: A three-wave time-lagged examination (2024)A novel evolutionary data mining algorithm with applications to churn prediction (2003)Customer churn prediction in the telecommunication sector using a rough set approach (2016)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM (2022)Customer Churn Prediction in Telecom Sector Using Machine Learning Techniques (2022)Deep Churn Prediction Method for Telecommunication Industry (2023)Multiclass Corporate Failure Prediction by Adaboost.M1 (2007)Hesitant fuzzy linguistic term sets for linguistic decision making: Current developments, issues and challenges (2017)Mixture of Activation Functions With Extended Min-Max Normalization for Forex Market Prediction (2019)Customer Segmentation Based on Machine Learning Methods (2024)VIRTSI: A novel trust dynamics model enhancing Artificial Intelligence collaboration with human users – Insights from a ChatGPT evaluation study (2024)Customer retention, loyalty, and satisfaction in the German mobile cellular telecommunications market (2001)New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy (2022)An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes (2023)Hyper-Personalization for Enhancing Customer Loyalty and Satisfaction in Customer Relationship Management (CRM) Systems (2023)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)Experimental Analysis of Hyperparameters for Deep Learning-Based Churn Prediction in the Banking Sector (2021)
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References

  • 2020Evaluating Trust Prediction and Confusion Matrix Measures for Web Services Ranking186 cited
  • 2020Churn Prediction in Telecommunication using Logistic Regression and Logit Boost160 cited
  • 2021Integrated Churn Prediction and Customer Segmentation Framework for Telco Business141 cited
  • 2015Telco Churn Prediction with Big Data130 cited
  • 2019Drivers for Pursuing Sustainability through IoT Technology within High-End Hotels—An Exploratory Study66 cited
  • 2018Customer Churn Prediction Modelling Based on Behavioural Patterns Analysis using Deep Learning59 cited
  • 2019Churn modeling with probabilistic meta paths-based representation learning19 cited
  • 2021Customer Decision Prediction Using Deep Neural Network on Telco Customer Churn Data15 cited

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