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AdaBoost Models for Corporate Bankruptcy Prediction with Missing Data · Study

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ArticleAdaBoost Models for Corporate Bankruptcy Prediction with Missing Data

Ligang Zhou2016

Article2016

AdaBoost Models for Corporate Bankruptcy Prediction with Missing Data

Ligang Zhou · Kin Keung Lai

47 citations·0/0 files stored·Computational Economics

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Imbalanced Data Classification Techniques

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References

1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1966Financial Ratios As Predictors of Failure 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 2001Forecasting Bankruptcy More Accurately: A Simple Hazard Model 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 2004Bankruptcy Prediction with Industry Effects 2004Neural network ensemble strategies for financial decision applications

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2022Application of Machine Learning Models for Predictions on Cross-Border Merger and Acquisition Decisions with ESG Characteristics from an Ecosystem and Sustainable Development Perspective 2023Evolutions in machine learning technology for financial distress prediction: A comprehensive review and comparative analysis

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Year2016

Typearticle

Published2016-04-21

VenueComputational Economics

ISSN-L0927-7099

Languageen

Citations47

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1007/s10614-016-9581-4

openalex_workW2337455698

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