Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting
This paper discusses the application of ensemble techniques for the prediction of time
series, presenting an in‐depth review of the main techniques and algorithms used by the …
series, presenting an in‐depth review of the main techniques and algorithms used by the …
Combining corporate governance indicators with stacking ensembles for financial distress prediction
In this paper, we use a stacking ensemble to construct a bankruptcy prediction model. We
collect a comprehensive list of 40 financial ratios (FRs) and 21 corporate governance …
collect a comprehensive list of 40 financial ratios (FRs) and 21 corporate governance …
A novel multi-stage ensemble model with enhanced outlier adaptation for credit scoring
W Zhang, D Yang, S Zhang, JH Ablanedo-Rosas… - Expert Systems with …, 2021 - Elsevier
Credit and credit-based transactions underlie the financial system. After decades of
development, artificial intelligence and machine learning have brought new momentum to …
development, artificial intelligence and machine learning have brought new momentum to …
An ensemble model for fake online review detection based on data resampling, feature pruning, and parameter optimization
J Yao, Y Zheng, H Jiang - Ieee Access, 2021 - ieeexplore.ieee.org
With the widespread of fake online reviews, the detection of fake reviews has become a hot
research issue. Despite the efforts of existing studies on fake review detection, the issues of …
research issue. Despite the efforts of existing studies on fake review detection, the issues of …
A new hybrid ensemble model with voting-based outlier detection and balanced sampling for credit scoring
W Zhang, D Yang, S Zhang - Expert Systems with Applications, 2021 - Elsevier
The credit scoring system has been revolutionized with the development of the financial
system and has received increasing attention from the academia and industry. Artificial …
system and has received increasing attention from the academia and industry. Artificial …
A novel method for credit scoring based on cost-sensitive neural network ensemble
W Yotsawat, P Wattuya, A Srivihok - IEEE Access, 2021 - ieeexplore.ieee.org
Most existing studies on credit scoring adapted a concept of classifier ensemble for solving
an imbalanced dataset. They apply resampling methods to generate multiple training …
an imbalanced dataset. They apply resampling methods to generate multiple training …
A novel framework for enhancing transparency in credit scoring: Leveraging Shapley values for interpretable credit scorecards
R Hlongwane, K Ramabao, W Mongwe - Plos one, 2024 - journals.plos.org
Credit scorecards are essential tools for banks to assess the creditworthiness of loan
applicants. While advanced machine learning models like XGBoost and random forest often …
applicants. While advanced machine learning models like XGBoost and random forest often …
Two-stage credit scoring using Bayesian approach
S Kyeong, J Shin - Journal of Big Data, 2022 - Springer
Commercial banks are required to explain the credit evaluation results to their customers.
Therefore, banks attempt to improve the performance of their credit scoring models while …
Therefore, banks attempt to improve the performance of their credit scoring models while …
A novel GSCI-based ensemble approach for credit scoring
X Chen, S Li, X Xu, F Meng, W Cao - IEEE Access, 2020 - ieeexplore.ieee.org
Credit scoring is an efficient tool for financial institutions to implement credit risk
management. In recent years, many novel machine learning models have been developed …
management. In recent years, many novel machine learning models have been developed …
Feature Enhanced Ensemble Modeling with Voting Optimization for Credit Risk Assessment
D Yang, B Xiao - IEEE Access, 2024 - ieeexplore.ieee.org
Machine learning methods have gained widespread utilization in small and micro enterprise
credit risk assessment. However, the practical application of these methods encounters a …
credit risk assessment. However, the practical application of these methods encounters a …