%0 Journal Article %A Damith Senanayake and Lakmal Muthugama and Laksheen Mendis and Tiroshan Madushanka %D 2015 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 99, 2015 %T Customer Churn Prediction: A Cognitive Approach %U https://publications.waset.org/pdf/10000977 %V 99 %X Customer churn prediction is one of the most useful areas of study in customer analytics. Due to the enormous amount of data available for such predictions, machine learning and data mining have been heavily used in this domain. There exist many machine learning algorithms directly applicable for the problem of customer churn prediction, and here, we attempt to experiment on a novel approach by using a cognitive learning based technique in an attempt to improve the results obtained by using a combination of supervised learning methods, with cognitive unsupervised learning methods. %P 767 - 773