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Forecasting bankruptcy using biclustering and neural network-based ensembles · Study

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ArticleForecasting bankruptcy using biclustering and neural network-based ensembles

Philippe du Jardin2019

Article2019

Forecasting bankruptcy using biclustering and neural network-based ensembles

Philippe du Jardin

42 citations·0/0 files stored·Annals of Operations Research

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Forecasting Techniques and Applications

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 1984A Further Empirical Investigation of the Bankruptcy Cost Question 2017Machine learning models and bankruptcy prediction 200535 years of studies on business failure: an overview of the classic statistical methodologies and their related problems 1996A survey of business failures with an emphasis on prediction methods and industrial applications 2002Predicting corporate financial distress: Reflections on choice-based sample bias

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2021Can earnings management information improve bankruptcy prediction models?2022Designing topological data to forecast bankruptcy using convolutional neural networks

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Year2019

Typearticle

Published2019-06-01

VenueAnnals of Operations Research

ISSN-L0254-5330

Languageen

Citations42

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1007/s10479-019-03283-2

openalex_workW2947933332

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