INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Customer Churn Prediction in Telecom Industry using FURIA and C4.5 algorithm
Authors Name:
Dayana Thomas
, Dr. Anitha Patil
Unique Id:
IJSDR1812001
Published In:
Volume 3 Issue 11, December-2018
Abstract:
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", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 11, page no.1 - 7, December-2018, Available :http://www.ijsdr.org/papers/IJSDR1812001.pdf
Downloads:
000337348
Publication Details:
Published Paper ID: IJSDR1812001
Registration ID:180864
Published In: Volume 3 Issue 11, December-2018
DOI (Digital Object Identifier):
Page No: 1 - 7
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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