Advances in machine learning modeling reviewing hybrid and ensemble methods

S Ardabili, A Mosavi, AR Várkonyi-Kóczy - International conference on …, 2019 - Springer
The conventional machine learning (ML) algorithms are continuously advancing and
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …

A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners

A Manzoor, MA Qureshi, E Kidney, L Longo - IEEE Access, 2024 - ieeexplore.ieee.org
Due to market deregulation and globalisation, competitive environments in various sectors
continuously evolve, leading to increased customer churn. Effectively anticipating and …

An efficient churn prediction model using gradient boosting machine and metaheuristic optimization

I AlShourbaji, N Helian, Y Sun, AG Hussien… - Scientific Reports, 2023 - nature.com
Customer churn remains a critical challenge in telecommunications, necessitating effective
churn prediction (CP) methodologies. This paper introduces the Enhanced Gradient …

A data-driven approach to improve customer churn prediction based on telecom customer segmentation

T Zhang, S Moro, RF Ramos - Future Internet, 2022 - mdpi.com
Numerous valuable clients can be lost to competitors in the telecommunication industry,
leading to profit loss. Thus, understanding the reasons for client churn is vital for …

TeKET: a Tree-Based Unsupervised Keyphrase Extraction Technique

G Rabby, S Azad, M Mahmud, KZ Zamli… - Cognitive …, 2020 - Springer
Automatic keyphrase extraction techniques aim to extract quality keyphrases for higher level
summarization of a document. Majority of the existing techniques are mainly domain …

Machine learning based customer churn prediction in home appliance rental business

Y Suh - Journal of big Data, 2023 - Springer
Customer churn is a major issue for large enterprises. In particular, in the rental business
sector, companies are looking for ways to retain their customers because they are their main …

Attention-based bi-directional long-short term memory network for earthquake prediction

MH Al Banna, T Ghosh, MJ Al Nahian, KA Taher… - IEEE …, 2021 - ieeexplore.ieee.org
An earthquake is a tremor felt on the surface of the earth created by the movement of the
major pieces of its outer shell. Till now, many attempts have been made to forecast …

Predicting customer churn: A systematic literature review

S De, P Prabu - Journal of Discrete Mathematical Sciences and …, 2022 - Taylor & Francis
Churn prediction is an active topic for research and machine learning approaches have
made significant contributions in this domain. Models built to address customer churn, aim to …

A novel approach to stance detection in social media tweets by fusing ranked lists and sentiments

AI Al-Ghadir, AM Azmi, A Hussain - Information Fusion, 2021 - Elsevier
Stance detection is a relatively new concept in data mining that aims to assign a stance label
(favor, against, or none) to a social media post towards a specific pre-determined target …

A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers

C Ieracitano, A Paviglianiti, M Campolo… - IEEE/CAA Journal of …, 2020 - ieeexplore.ieee.org
The manufacturing of nanomaterials by the electrospinning process requires accurate and
meticulous inspection of related scanning electron microscope (SEM) images of the …