With the increase in the adoption rate of machine learning algorithms in multiple sectors, the
need for accurate measurement and assessment is imperative, especially when classifiers …

Scores of researchers have paid attention to empirical and conceptual dimensions of
Customer relationship management (CRM). A few studies summarise the research output of …

Applying machine learning in real-world applications may have various implications on
companies, but individuals as well. Besides obtaining lower costs, faster time to decision …

Non-contractual setting and many brands and alternative products make customer retention
relatively more difficult in the FMCG market. Besides, there is no absolute customer loyalty …

With increasingly fierce competition in other transportation markets, the customer churn in
railway freight becomes a very serious problem. Facing the high similarity and …

Customer experience plays a critical role for a profitable organisation or company. A
satisfied customer for a company corresponds to higher rates of customer retention, and …

On a scarce-data customer churn prediction problem, using the tiny differences between the
predictions of (1) the single-best model and (2) the ensemble from Bayesian model …

Customer churn prediction is crucial for businesses in different industries, such as
telecommunications, banking, insurance and e-commerce, because acquiring new …

Nowadays, churn prediction is the most common Big Data application in the telecoms
industry, However, the characteristic of unbalanced classes in this kind of application opens …

Performance tuning of the machine learning models is very important, especially in the
banking domain. In line with the new age, they are moving away from their conventional …