@article{(Open Science Index):https://publications.waset.org/pdf/10000977,
	  title     = {Customer Churn Prediction: A Cognitive Approach},
	  author    = {Damith Senanayake and  Lakmal Muthugama and  Laksheen Mendis and  Tiroshan Madushanka},
	  country	= {},
	  institution	= {},
	  abstract     = {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
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {3},
	  year      = {2015},
	  pages     = {767 - 773},
	  ee        = {https://publications.waset.org/pdf/10000977},
	  url   	= {https://publications.waset.org/vol/99},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 99, 2015},