Results 81 to 90 of about 1,692 (204)

Explainable AI With Imbalanced Learning Strategies for Blockchain Transaction Fraud Detection

Engineering Reports, Volume 8, Issue 1, January 2026.
Research methodology pipeline for blockchain fraud detection. ABSTRACT Blockchain networks now support billions of dollars in daily transactions, making reliable and transparent fraud detection essential for maintaining user trust and financial stability.
Ahmed Abbas Jasim Al‐Hchaimi, M. A. Khalifa, Walid El‐Shafai   +2 more
wiley   +1 more source

Identifying customers likely to churn

, 2008
As acquiring new customers is costly, it seems logical to keep and satisfy long-time customers rather than to acquire new customers. To reduce churn rates, firms should manage customers proactively to avoid losing churned customers.
Jarvis, W., Zorn, S., Bellman, S.
core  

Explaining customer churn prediction in telecom industry using tabular machine learning models

Machine Learning with Applications
The study addresses customer churn, a major issue in service-oriented sectors like telecommunications, where it refers to the discontinuation of subscriptions.
Sumana Sharma Poudel, Suresh Pokharel, Mohan Timilsina   +2 more
doaj   +1 more source

Predicting Customer Churn

, 2022
The focus of this project is in predicting customer churn. It is essential to consider and handle the imbalance problem, that is why this project explains the imbalance problem, states its importance and presents some methods to handle it. It continues to describe the algorithms of three classification algorithms; logistic regression, classification ...
openaire   +1 more source

Customer Churn in Subscription Business Model—Predictive Analytics on Customer Churn

BCP Business & Management, 2023
There is a growing tendency for more companies to develop towards a subscription business model. Under such a trend, it is important to learn about the customer churn rate within the business, learn from it and adjust business strategies accordingly.
openaire   +1 more source

Bagging and boosting classification trees to predict churn. [PDF]

In this paper, bagging and boosting techniques are proposed as performing tools for churn prediction. These methods consist of sequentially applying a classification algorithm to resampled or reweigthed versions of the data set. We apply these algorithms
Croux, Christophe, Lemmens, Aurélie
core  

E-commerce big data processing based on an improved RBF model

Journal of Intelligent Systems
In the dynamic landscape of China’s booming economy, the surge in e-commerce customer volume presents both opportunities and challenges, notably in managing customer churn (CC). Addressing this critical issue, this study introduces an innovative approach
Lu Qiuping
doaj   +1 more source

Research on Customer Churn Prediction Using Machine Learning Models [PDF]

SHS Web of Conferences
The percentage of consumers or subscribers that discontinue using a product or service within a given time frame is known as the “churn rate.” Hence, using machine learning models to estimate the number of possible churn consumers is crucial for ...
Jia Xiaolei
doaj   +1 more source

Agent based modelling and simulation: An examination of customer retention in the UK mobile market

, 2012
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Customer retention is an important issue for any business, especially in mature markets such as the UK mobile market where new customers can only be ...
Hassouna, Mohammed Bassam
core  

A comprehensive survey on customer churn analysis studies

Journal of Information and Telecommunication
This paper presents a comprehensive survey of customer churn analysis studies. It begins by examining the customer journey and touchpoints, emphasizing their influence on churn behaviour.
Maryam Shahabikargar, Amin Beheshti, Xuyun Zhang, Jin Foo, Alireza Jolfaei   +4 more
doaj   +1 more source