Results 101 to 110 of about 9,090 (181)

A novel classification algorithm for customer churn prediction based on hybrid Ensemble-Fusion model. [PDF]

Sci Rep
He C, Ding CHQ.
europepmc   +1 more source

Early warning of telecom enterprise customer churn based on ensemble learning. [PDF]

PLoS One, 2023
Zhou Y, Chen W, Sun X, Yang D.
europepmc   +1 more source

Application of GWO-attention-ConvLSTM model in customer churn prediction and satisfaction analysis in customer relationship management. [PDF]

Heliyon
Zhang H, Zhang W.
europepmc   +1 more source

Negative correlation learning for customer churn prediction: a comparison study. [PDF]

ScientificWorldJournal, 2015
Rodan A, Fayyoumi A, Faris H, Alsakran J, Al-Kadi O.   +4 more
europepmc   +1 more source

Customer retention and churn prediction in the telecommunication industry: a case study on a Danish university. [PDF]

SN Appl Sci, 2023
Saleh S, Saha S.
europepmc   +1 more source

An efficient churn prediction model using gradient boosting machine and metaheuristic optimization. [PDF]

Sci Rep, 2023
AlShourbaji I, Helian N, Sun Y, Hussien AG, Abualigah L, Elnaim B.   +5 more
europepmc   +1 more source

Customer Churn Prediction Using Machine Learning

INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Abstract - In today’s highly competitive telecom sector, customer churn — the loss of clients to competitors — poses a major threat to revenue and growth. This project tackles churn prediction using machine learning, focusing on the Random Forest algorithm to identify customers likely to leave.
openaire   +1 more source

Predicting customer churn using Machine Learning

Customer churn can be defined as the phenomenon of customers who discontinue their relationship with a company. This problem is transversal to many industries, including the software industry. This study uses Machine Learning to build a predictive model to identify potential churners in a Portuguese software house.
Dias, João Pedro Rolim, António, Nuno   +1 more
openaire   +1 more source

Classification of customer retention using hybrid SVC-SDNN to enhance customer relationship management. [PDF]

PLoS One
Ishaq M, Yaqub N, Fayaz M, Khan A, Saidani T, Saidani O.   +5 more
europepmc   +1 more source

Neural network approach enhancing churn prediction with categorical encoding and standard scaling. [PDF]

Sci Rep
Bhattacharjee B, Madhu U, Guha SK, Bhadra S, Das PK, Samantaray SP, Zubairuddin M, Tamboli S.   +7 more
europepmc   +1 more source