Results 71 to 80 of about 9,240 (196)
Case studies in applying data mining for churn analysis [PDF]
, 2017 The advent of price and product comparison sites now makes it even more important to retain customers and identify those that might be at risk of leaving. The use of data mining methods has been widely advocated for predicting customer churn.
C.-F.Tsai +6 more
core +1 more source
CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 447-463, April 2026.ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim +4 more
wiley +1 more source
Prediction of Customer Churn in Banking Industry
CoRR, 2020 With the growing competition in banking industry, banks are required to follow customer retention strategies while they are trying to increase their market share by acquiring new customers. This study compares the performance of six supervised classification techniques to suggest an efficient model to predict customer churn in banking industry, given ...
openaire +2 more sources
Corporate ESG Profiles and Investor Horizons
The Journal of Finance, Volume 81, Issue 2, Page 603-642, April 2026.ABSTRACT We find that long‐term institutional investors tilt their portfolios toward firms with better Environmental, Social, and Governance (ESG) profiles, in the cross sections of both institutional investor portfolios and the ownership of firms. We test whether several theoretically motivated mechanisms can explain this relationship.
LAURA T. STARKS, PARTH VENKAT, QIFEI ZHU
wiley +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 +3 more sources
Location‐Based Accessibility and Innovation Performance
Journal of Regional Science, Volume 66, Issue 2, Page 376-398, March 2026.ABSTRACT While the importance of local characteristics for innovation activities has been studied extensively, it remains largely unknown to which extent better transport‐based accessibilities facilitate innovation. This study builds on data from a Germany‐wide agent‐based transport model to derive local accessibilities for different modes of transport
Linda Bandelow, Hanna Hottenrott
wiley +1 more source
Handling class imbalance in customer churn prediction [PDF]
Expert Systems with Applications, 2009 Customer churn is often a rare event in service industries, but of great interest and great value. Until recently, however, class imbalance has not received much attention in the context of data mining [Weiss, G. M. (2004). Mining with rarity: A unifying framework. SIGKDD Explorations, 6(1), 7-19]. In this study, we investigate how we can better handle
Jonathan Burez, Dirk Van den Poel
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British Educational Research Journal, Volume 52, Issue 1, Page 481-516, February 2026.Abstract Higher education in the United Kingdom has dramatically expanded in recent decades, along with questions about its effectiveness in preparing graduates for the labour market. With rising tuition fees and increasing competition for graduate jobs, many students opt to study ‘professional’ subjects—fields closely tied to specific professions ...
Sarah Pemberton
wiley +1 more source
A century of art dealing in New York. The rise of American art
The Economic History Review, Volume 79, Issue 1, Page 281-311, February 2026.Abstract We study art trade in New York between 1870 and 1970, analysing returns on investment by the renowned Knoedler gallery to shed light on the evolution of the American art market. A generalist art gallery should allocate investments to equalize expected returns, with differences in effective returns depending on purchase prices, number of traded
Federico Etro, Elena Stepanova
wiley +1 more source
Journal of Big DataClass imbalance is one of many problems of customer churn datasets. One of the common problems is class overlap, where the data have a similar instance between classes.
I Nyoman Mahayasa Adiputra +1 more
doaj +1 more source