Telecommunication Services Churn Prediction - Deep Learning Approach

Mirjana Karanovic · Milivoje Popovac · Srdjan Sladojević · Marko Arsenović · Darko Stefanović

22 citations0/0 files storedTelecommunications Forum (TELFOR)

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Customer churn and segmentation Customer Service Quality and Loyalty AI and HR Technologies

Abstract

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.

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2015A Multi-Layer Perceptron Approach for Customer Churn Prediction 2017Designing of customer and employee churn prediction model based on data mining method and neural predictor 2016Churn analysis using deep convolutional neural networks and autoencoders 2017Analysis of imbalanced data set problem: The case of churn prediction for telecommunication 2017Churn prediction in telecommunication using machine learning

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2023Machine Learning and Deep Learning technique used in Customer Churn Prediction: - A Review 2022Deep Convolutional Neural Network Based Churn Prediction for Telecommunication Industry 2022Analysis of customer churn prediction using machine learning and deep learning algorithms 2022Development of fading channel patch based convolutional neural network models for customer churn prediction 2024Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction 2021Design and Implementation of a System for Comparative Analysis of Learning Architectures for Churn Prediction

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