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Showing 1 to 11 of 11 for “"Churn Prediction"”.

  1. Machine Learning Methods for Churn Prediction and Infrastructure Resilience

    … telecommunications industry: short-term customer churn prediction and long-term infrastructure resilience to climate-driven disruptions. In the first part of this work, I develop an upgrades-informed churn forecasting model tailored specifically for marketing operations. Recognizing limitations in …

    mit Repository record for Machine Learning Methods for Churn Prediction and Infrastructure Resilience (opens in a new tab)

  2. Machine Learning Approach for Churn Prediction in a Mobile App

    … el problema crítico de la pérdida de usuarios o "churn" en la industria de aplicaciones móviles. La tesis argumenta que en lugar de solo enfocarse en adquirir nuevos usuarios, las empresas de aplicaciones móviles deben centrarse en retener a los existentes para reducir la tasa de churn. La tasa de …

    utdt Repository record for Machine Learning Approach for Churn Prediction in a Mobile App (opens in a new tab)

  3. Enhancing Telecom Churn Prediction: Adaboost with Oversampling and Recursive Feature Elimination Approach

    <p>Churn prediction is a critical task for businesses to retain their valuable customers. This paper presents a comprehensive study of churn prediction in the telecom sector using 15 approaches, including popular algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random …

    calpoly Repository record for Enhancing Telecom Churn Prediction: Adaboost with Oversampling and Recursive Feature Elimination Approach (opens in a new tab)

  4. Comparison of Classification Algorithms and Undersampling Methods on Employee Churn Prediction: A Case Study of a Tech Company

    <p>Churn prediction is a common data mining problem that many companies face across industries. More commonly, customer churn has been studied extensively within the telecommunications industry where there is low customer retention due to high market competition. Similar to customer churn, employee …

    calpoly Repository record for Comparison of Classification Algorithms and Undersampling Methods on Employee Churn Prediction: A Case Study of a Tech Company (opens in a new tab)

  5. The Many Types of Churn and Their Predictive Models

    … account of customer, business and employee churn and how each of these churn types have been studied in extant literature. Consequently, a more comprehensive definition of churn that is grounded on the notion of various types of partnerships (B2C, B2B and B2E) is presented. Additionally, a …

    creighton Repository record for The Many Types of Churn and Their Predictive Models (opens in a new tab)

  6. The use of artificial intelligence for business optimisation in banking: case of Nigeria

    … analysis, customer segmentation, customer churn prediction, predicting loan collection credibility and product recommendations. Findings also show that deep learning models were not used by the commercial banks, due in part to a lack of computational resources Contribution: The research …

    cape-town Repository record for The use of artificial intelligence for business optimisation in banking: case of Nigeria (opens in a new tab)

  7. Building well-performing classifier ensembles: model and decision level combination.

    … performance from classification systems, and prediction systems in general. Ensemble methods, or the combining of multiple classifiers, have become an accepted and successful tool for doing this, though the reasons for success are not always entirely understood. In this thesis, we review the …

    bournemouth Repository record for Building well-performing classifier ensembles: model and decision level combination. (opens in a new tab)