Results 111 to 120 of about 1,523,124 (234)

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

Long‐Term Institutional Investors and Executive Compensation

Financial Review, Volume 61, Issue 4, Page 1317-1345, November 2026.
ABSTRACT Standard agency theory views would suggest that long‐term investors will use long‐term CEO compensation to align incentives and promote long‐term value maximization. An alternative view is that long‐term investors—who are more able to bear the fixed costs associated with monitoring—will monitor more heavily than short‐term investors, reducing ...
T. Colin Campbell, Haimanot Kassa, Timothy E. Trombley   +2 more
wiley   +1 more source

Modelli di Churn Prediction [PDF]

, 2010
La tesi si pone l’obiettivo di descrivere il tema della churn prediction, che consiste nella previsione dello spostamento dei clienti da un’azienda all’altra.
PORRECA, ROSARIO
core  

How Are “Financial Balances” Financed? Wicksell, (Keynes) and the US Mainstream Don't Fit Today's Institutions; Kalecki, Triffin, and Minsky Got it Right

Metroeconomica, Volume 77, Issue 4, Page 310-325, November 2026.
ABSTRACT The paper examines the financial balances of the US economy. Government is the main borrower and households and the foreign sector the main lenders. Business net lending is minimal. The balances and their underlying transactions contradict the loanable funds theory and its “global savings glut” variation.
Michalis Nikiforos, Lance Taylor
wiley   +1 more source

CTGAN-ENN: a tabular GAN-based hybrid sampling method for imbalanced and overlapped data in customer churn prediction

Journal of Big Data
Class 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, Paweena Wanchai   +1 more
doaj   +1 more source

A Data Imputation Strategy to Enhance Online Game Churn Prediction, Considering Non-Login Periods

Data
User churn in online games refers to players becoming inactive for an extended period. Even a small increase in churn can lead to significant revenue loss, making churn prediction crucial for sustaining long-term player engagement.
JaeHong Lee, Pavinee Rerkjirattikal, SangGyu Nam   +2 more
doaj   +1 more source

Research on customer churn prediction and model interpretability analysis. [PDF]

PLoS One, 2023
Peng K, Peng Y, Li W.
europepmc   +1 more source

Access to Safety Net Programs in the U.S. During the COVID‐19 Pandemic: Barriers and Lessons From a Scoping Review

Social Policy &Administration, Volume 60, Issue 6, Page 1013-1035, November 2026.
ABSTRACT The COVID‐19 pandemic triggered historic expansions of the U.S. social safety net to mitigate unprecedented economic hardship. However, increased government spending and program expansions on paper do not automatically translate into equitable access in practice.
Soohyun Yoon, Jeehae Kang
wiley   +1 more source

Customer churn prediction using composite deep learning technique. [PDF]

Sci Rep, 2023
Khattak A, Mehak Z, Ahmad H, Asghar MU, Asghar MZ, Khan A.   +5 more
europepmc   +1 more source

Applying CHAID for logistic regression diagnostics and classification accuracy improvement [PDF]

In this study a CHAID-based approach to detecting classification accuracy heterogeneity across segments of observations is proposed. This helps to solve some important problems, facing a model-builder: 1. How to automatically detect segments in which the
Antipov, Evgeny, Pokryshevskaya, Elena
core