This paper explores the application of various machine learning techniques for predicting
customer churn in the telecommunications sector. We utilized a publicly accessible dataset …

With the upsurge of data traffic due to the change in customer behavior towards the use of
telecommunications services, fostered by the current global health situation (mainly due to …

The customer churn prediction (CCP) is one of the challenging problems in the telecom
industry. With the advancement in the field of machine learning and artificial intelligence, the …

Customer retention campaigns increasingly rely on predictive analytics to identify potential
churners in a customer base. Traditionally, customer churn prediction was dependent on …

This study proposed an ECG (Electrocardiogram) classification approach using machine
learning based on several ECG features. An electrocardiogram (ECG) is a signal that …

Without proper analysis and forecasting, industries will find themselves repeatedly churning
customers, which the telecom industry in particular cannot afford. A predictable model for …

Customer churn is one of the most challenging problems that affects revenue and customer
base in mobile telecom operators. The success of retention campaigns depends not only on …

Customer churn is a complex challenge for burgeoning competitive organizations,
especially in telecommunication. It refers to customers that swiftly leave a company for a …

Being able to predict the churn rate is the key to success for the telecommunication industry.
It is also important for the telecommunication industry to obtain a high profit. Thus, the …

Businesses must compete fiercely to win over new consumers from suppliers. Since it
directly affects a company's revenue, client retention is a hot topic for analysis, and early …