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Application of machine learning algorithms for business failure prediction
16 references·1 citing·29 second hop
Application of machine learning algorithms for business failure prediction (2017)Application of machine learning algorithm…Using Bayesian networks for bankruptcy prediction: Some methodological issues (2006)Using Bayesian networks for b…Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Bankruptcy prediction using s…An application of support vector machines in bankruptcy prediction model (2004)An application of support vec…A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction (2002)A case-based reasoning with t…Bankruptcy prediction for credit risk using neural networks: A survey and new results (2001)Bankruptcy prediction for cre…Probabilistic Neural Networks in Bankruptcy Prediction (1999)Probabilistic Neural Networks…Genetic algorithms applications in the analysis of insolvency risk (1998)Genetic algorithms applicatio…A k-Nearest-Neighbour Classifier for Assessing Consumer Credit Risk (1996)A k-Nearest-Neighbour Classif…Recognizing Financial Distress Patterns Using a Neural Network Tool (1993)Recognizing Financial Distres…Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Managerial Applications of Ne…A neural network model for bankruptcy prediction (1990)A neural network model for ba…Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data (1988)Inducing Rules for Expert Sys…Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress (1985)Introducing Recursive Partiti…The Experimental Design of Classification Models: An Application of Recursive Partitioning and Bootstrapping to Commercial Bank Loan Classifications (1984)The Experimental Design of Cl…Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Financial Ratios and the Prob…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Financial Disclosures by Using Machine Learning Analysis (2021)Financial Disclosures by Usin…Financial Ratios As Predictors of Failure (1966)ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)An application of the cox proportional hazards model to bank failure (1986)A survey of business failures with an emphasis on prediction methods and industrial applications (1996)Predicting corporate financial distress: Reflections on choice-based sample bias (2002)Experiments in induction (1966)Human Problem Solving (1972)Hybrid neural network models for bankruptcy predictions (1996)Dynamics of Modeling in Data Mining: Interpretive Approach to Bankruptcy Prediction (1999)50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science (2004)Conditional logit analysis of qualitative choice behavior (1972)The Effect of Audit Quality on Earnings Management* (1998)Forecasting Bankruptcy More Accurately: A Simple Hazard Model (2001)Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)Credit risk measurement: Developments over the last 20 years (1997)Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks (1998)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)Positive Accounting Theory (1985)Designing a neural network for forecasting financial and economic time series (1996)Forecasting with artificial neural networks: (1998)Neural network credit scoring models (2000)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Using neural network ensembles for bankruptcy prediction and credit scoring (2007)CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE (2011)Consumer credit-risk models via machine-learning algorithms (2010)Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Managerial incentives and risk-taking☆ (2005)How does financial reporting quality relate to investment efficiency? (2009)
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References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy6,005 cited
  • 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions1,121 cited
  • 2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters872 cited
  • 1990A neural network model for bankruptcy prediction853 cited
  • 2004An application of support vector machines in bankruptcy prediction model809 cited
  • 1985Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress748 cited
  • 2001Bankruptcy prediction for credit risk using neural networks: A survey and new results696 cited
  • 1993Recognizing Financial Distress Patterns Using a Neural Network Tool470 cited
  • 1988Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data289 cited
  • 1996A k-Nearest-Neighbour Classifier for Assessing Consumer Credit Risk286 cited
  • 1999Probabilistic Neural Networks in Bankruptcy Prediction277 cited
  • 2002A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction277 cited
  • 1998Genetic algorithms applications in the analysis of insolvency risk

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269 cited
  • 2006Using Bayesian networks for bankruptcy prediction: Some methodological issues170 cited
  • 1984The Experimental Design of Classification Models: An Application of Recursive Partitioning and Bootstrapping to Commercial Bank Loan Classifications156 cited
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    • 2021Financial Disclosures by Using Machine Learning Analysis8 cited