A comparison of machine learning techniques for customer churn prediction
Machine Learning is a Computer Science sector that is concerned with the design and development of algorithms that allow the automated performance of tasks like pattern recognition, prediction, diagnosis, etc., based on empirical data. Therefore, Machine Learning plays a key role in the development of business data mining applications in various fields such as retail, marketing, banking, and telecommunications.
Machine Learning algorithms and tools are an essential part of mSensis’ R&D, aiming to enhance its products and services with state-of-the-art applications like predictive analytics, (social) recommender systems, churn and risk prediction systems, among others.
A result of this ongoing research is the scientific paper “A Comparison of Machine Learning Techniques for Customer Churn Prediction” published in the academic journal “Simulation Modeling Practice and Theory-Elsevier”.
The abovementioned research was supported by the ICT4GROWTH action of the Information Society S.A., which invests in projects related to the design, development and commercialization of innovative products and value-added services, in the field of Information and Communication Technologies (ICT).
To access the abstract and the full text of the paper, please refer to: http://dx.doi.org/10.1016/j.simpat.2015.03.003