Customer Churn Prediction in Telecom Industry using FURIA and C4.5 algorithm
Dayana Thomas
, Dr. Anitha Patil
Keywords — Churn Prediction; CRM (Customer Relationship Management); FURIA (Fuzzy Unordered Rule Induction Algorithm); C4.5 algorithm.
Abstract—Nowadays, Customer churn prediction in Telecom industry is one of the most important research topics. Customer churn is a condition of switching from one service provider to another by a customer. Telecommunication companies face considerable loss of revenue, because some of the customers who are at risk of leaving a company. Customer churn prediction is a foremost feature of contemporary telecom CRM systems. Churn prediction system helps the customer relationship management to retain the customers who are probable to quit. In this paper, we propose a highly sophisticated model using Fuzzy Unordered Rule Induction Algorithm FURIA and C4.5 algorithm to predict the customer churn in telecom industry. FURIA extends the well known RIPPER algorithm, a state-of-the-art rule learner. FURIA learns fuzzy rules instead of conventional rules and unordered rule sets instead of rule lists. Therefore, the proposed model is capable of predicting customers churn behavior well in advance with more accuracy. The FURIA has less execution time compared to the previous research. And also the FURIA outperforms decision tree and other models in terms of accuracy, precision and recall and has the ability to identify the maximum churners for retention campaigns.
"Customer Churn Prediction in Telecom Industry using FURIA and C4.5 algorithm", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 11, page no.1 - 7, December-2018, Available :https://ijsdr.org/papers/IJSDR1812001.pdf
Volume 3
Issue 11,
December-2018
Pages : 1 - 7
Paper Reg. ID: IJSDR_180864
Published Paper Id: IJSDR1812001
Downloads: 000347195
Research Area: Engineering
Country: New Panvel, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
