1 publication

• Published Subscription Review Article 1 Aug 2024

  Customer Churn Prediction Using ML Algorithms

  By Prajwal Waghole, Kalpna Saharan, Varad Wanwase, Shantanu Wasnik, Rajratan Gokhale

  Abstract: Comprehending customer churn is essential for businesses aiming to enhance and sustain customer relationships. This study introduces a machine learning approach aimed at forecasting customer churn by leveraging demographic and behavioral data. Our research involved developing predictive models using support vector machines (SVM), random forests, and decision trees, evaluating their efficacy using real-world data from the telecom industry. Our findings underscore that random forests consistently outperform SVM and decision trees …

  Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 70–75 Read article →