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Ensemble learning with label proportions for bankruptcy prediction · Study

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ArticleEnsemble learning with label proportions for bankruptcy prediction

Zhensong Chen2019

Article2019

Ensemble learning with label proportions for bankruptcy prediction

Zhensong Chen · Wei Chen · Yong Shi

81 citations·0/0 files stored·Expert Systems with Applications

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Financial Distress and Bankruptcy Prediction Machine Learning and Data Classification Imbalanced Data Classification Techniques

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 2017Machine learning models and bankruptcy prediction 2004An application of support vector machines in bankruptcy prediction model 2014Proceedings of the 22nd ACM international conference on Multimedia 2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm 2001Bankruptcy prediction for credit risk using neural networks: A survey and new results 2013Measuring firm performance using financial ratios: A decision tree approach 2016Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study

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2020The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm 2024Machine learning in business and finance: a literature review and research opportunities 2022Systematic Review of Financial Distress Identification using Artificial Intelligence Methods 2021Opening the black box – Quantile neural networks for loss given default prediction

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Details

Year2019

Typearticle

Published2019-12-23

VenueExpert Systems with Applications

ISSN-L0957-4174

Languageen

Citations81

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1016/j.eswa.2019.113155

openalex_workW2997325425

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2024

Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction

2021Company bankruptcy prediction framework based on the most influential features using XGBoost and stacking ensemble learning

2022Predicting and interpreting financial distress using a weighted boosted tree-based tree

2021CORPORATE BANKRUPTCY AND INSOLVENCY PREDICTION MODEL