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A Data Driven Ensemble Classifier for Credit Scoring Analysis
11 references·0 citing·37 second hop
A Data Driven Ensemble Classifier for Credit Scoring Analysis (2009)A Data Driven Ensemble Classifier for Cre…Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Using neural network ensemble…Using Bayesian networks for bankruptcy prediction: Some methodological issues (2006)Using Bayesian networks for b…Credit scoring with a data mining approach based on support vector machines (2006)Credit scoring with a data mi…Hybrid mining approach in the design of credit scoring models (2005)Hybrid mining approach in the…Predicting corporate failure: empirical evidence for the UK (2004)Predicting corporate failure:…Neural network ensemble strategies for financial decision applications (2004)Neural network ensemble strat…Rough sets bankruptcy prediction models versus auditor signalling rates (2003)Rough sets bankruptcy predict…Bayesian Models for Early Warning of Bank Failures (2001)Bayesian Models for Early War…A Multinomial Logit Analysis of Problem Loan Resolution Choices in Banking (1995)A Multinomial Logit Analysis …Neural Networks: A New Tool for Predicting Thrift Failures* (1992)Neural Networks: A New Tool f…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Limited-dependent and qualitative variables in econometrics (1983)How effective are neural networks at forecasting and prediction? A review and evaluation (1998)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)Financial Ratios As Predictors of Failure (1966)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)A data driven ensemble classifier for credit scoring analysis (2009)Predicting business failure using classification and regression tree: An empirical comparison with popular classical statistical methods and top classification mining methods (2010)Partial Least Square Discriminant Analysis for bankruptcy prediction (2012)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) (1994)Neural network credit scoring models (2000)An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring (2008)Comparative analysis of data mining methods for bankruptcy prediction (2011)Machine Learning in Financial Crisis Prediction: A Survey (2011)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE (2011)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)Credit rating by hybrid machine learning techniques (2009)Combining cluster analysis with classifier ensembles to predict financial distress (2011)Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring (2019)Early warning of bank failure (1977)Risk in Banking and Capital Regulation (1988)Order effects in belief updating: The belief-adjustment model (1992)Effects of feature construction on classification performance: An empirical study in bank failure prediction (2008)Dynamic Interpretation of Emerging Risks in the Financial Sector (2019)Deciding the financial health of dot-coms using rough sets (2006)Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction (2010)Forecasting business failure: The use of nearest-neighbour support vectors and correcting imbalanced samples – Evidence from the Chinese hotel industry (2011)Bankruptcy prediction using terminal failure processes (2014)Systematic review of bankruptcy prediction models: Towards a framework for tool selection (2017)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Machine behaviour (2019)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
  • 2006Credit scoring with a data mining approach based on support vector machines805 cited
  • 1992Neural Networks: A New Tool for Predicting Thrift Failures*533 cited
  • 2007Using neural network ensembles for bankruptcy prediction and credit scoring514 cited
  • 2004Predicting corporate failure: empirical evidence for the UK429 cited
  • 2004Neural network ensemble strategies for financial decision applications332 cited
  • 2005Hybrid mining approach in the design of credit scoring models196 cited
  • 2006Using Bayesian networks for bankruptcy prediction: Some methodological issues170 cited
  • 2001Bayesian Models for Early Warning of Bank Failures155 cited
  • 2003Rough sets bankruptcy prediction models versus auditor signalling rates107 cited
  • 1995A Multinomial Logit Analysis of Problem Loan Resolution Choices in Banking76 cited

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