STACKING ENSEMBLE APPROACH FOR CHURN PREDICTION: INTEGRATING CNN AND MACHINE LEARNING MODELS WITH CATBOOST META-LEARNER

Stacking Ensemble Approach for Churn Prediction: Integrating CNN and Machine Learning Models with CatBoost Meta-Learner

In the telecom industry, predicting customer churn is crucial for improving customer retention.In literature, the use of single classifiers is predominantly focused.Customer data is complex data due to class read more imbalance and contain multiple factors that exhibit nonlinear dependencies.In these complex scenarios, single classifiers may be una

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EMC3-EIRENE simulations of edge plasma and impurity transport by toroidally localized argon seeding on CFETR X-divertor

The three-dimensional (3D) edge Monte Carlo transport code EMC3-EIRENE has been employed to study edge plasma and impurity transport with toroidally localized argon seeding using the Chinese fusion engineering testing reactor (CFETR) X-divertor configuration.The argon impurity seeded at different poloidal locations was investigated to evaluate the

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Optimization of the Solid Cardboard in Carton Design

The present research aimed to increase the accuracy of predicting the maximum force required to compress a solid cardboard box.Changes in the technology of solid cardboard production and the design of packaging help to increase the durability of packaging; however, typical estimation methods do not take these changes into account.By determining the

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The effect of problems on supply chain wide efficiency

For any business to compete successfully in the modern, globalised business environment, it needs to mobilise its suppliers and customers to co-operate in order to reduce unnecessary costs and inefficiencies between them and to ensure the best value for the final customer.The focus is on management of the supply chain as a apac1/60/1/cw whole (or a

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