Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/1853
Title: Telecommunication Services Churn Prediction - Deep Learning Approach
Authors: Karanović, Mirjana 
Popovac M.
Sladojević, Srđan 
Arsenović, Marko 
Stefanović, Darko 
Issue Date: 1-Jan-2018
Journal: 2018 26th Telecommunications Forum, TELFOR 2018 - Proceedings
Abstract: © 2018 IEEE. Churn is a phenomenon that concerns the majority of companies, especially in the telecommunication industry. This paper describes experiment on data provided by the telecommunications company - Orange, for predicting churn. The preprocessing phase of the experiment included removal of missing values and redundant data, Lasso and manual feature engineering. Convolutional Neural Network was applied as classifier on preprocessed one-dimensional dataset with accuracy of 98.85%. Proposed model can be applicable in telecommunication systems for detection.
URI: https://open.uns.ac.rs/handle/123456789/1853
ISBN: 9781538671702
DOI: 10.1109/TELFOR.2018.8612067
Appears in Collections:FTN Publikacije/Publications

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