predictive modeling

2 articles · search the full text for this term

• Published Subscription 20 Nov 2024

  Machine Learning Approaches for Customer Churn Prediction in Telecommunications

  By Anjali Banarase, Ruchi Dave, Vaishnavi Chavan, Kajal Bhagwat

  Abstract: Customer churn prediction is a critical challenge for companies in the telecommunications industry. The competition is intense, and acquiring new customers can be costly. Predicting when existing customers might leave (churn) helps companies take proactive measures to retain them, reducing churn rates and costs. By analyzing historical customer data, including demographics, service usage, billing, and customer service interactions, this study aims to identify customers at risk of leaving their current …

  Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–7 Read article →

• Published Subscription 8 Oct 2024

  Unveiling Employee Attrition: Harnessing Predictive Modeling for Proactive Workforce Management

  By Anjali Sharma, Prabuddha Tamhane, Priyanshi Golatkar, Shreyy Sharma, Vaidehi Shah, Aditya Kasar

  Abstract: This study aims to predict employee turnover and identify organizational factors contributing to attrition by employing predictive analytics techniques. Employee attrition, which refers to the loss of employees without immediate replacements, leads to reduced overall workforce productivity. The study evaluates different machine learning techniques, such as gradient boosting, random forest, and logistic regression, to identify employees who are most likely to leave, and uses SPSS software to ensure the reliability …

  Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 1–10 Read article →