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ArticleBusiness health characterization: A hybrid regression and support vector machine analysis

Rudrajeet Pal2015

Article2015

Business health characterization: A hybrid regression and support vector machine analysis

Rudrajeet Pal · Jiřı́ Militký

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

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

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1966Financial Ratios As Predictors of Failure 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters 2004An application of support vector machines in bankruptcy prediction model 2013Predicting financial distress of companies: revisiting the Z-Score and ZETA® models 200535 years of studies on business failure: an overview of the classic statistical methodologies and their related problems 1995The Anatomy of the Performance of Buy and Sell Recommendations

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2019Rough set-based feature selection for credit risk prediction using weight-adjusted boosting ensemble method 2021Explanatory Factors of Business Failure: Literature Review and Global Trends 2019Predicting firm failure in the software industry 2021Applications of machine learning for corporate bond yield spread forecasting 2023RETRACTED ARTICLE: Enhancing Financial Risk Prediction for Listed Companies: A Catboost-Based Ensemble Learning Approach

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Details

Year2015

Typearticle

Published2015-12-18

VenueExpert Systems with Applications

ISSN-L0957-4174

Languageen

Citations36

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1016/j.eswa.2015.11.027

openalex_workW2251898997

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2020MACHINE LEARNING IN BANKRUPTCY PREDICTION – A REVIEW