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Neighborhood rough set and SVM based hybrid credit scoring classifier
8 references·16 citing·41 second hop
Neighborhood rough set and SVM based hybrid credit scoring classifier (2011)Neighborhood rough set and SVM based hybr…Hybrid mining approach in the design of credit scoring models (2005)Hybrid mining approach in the…Credit scoring and rejected instances reassigning through evolutionary computation techniques (2003)Credit scoring and rejected i…Credit scoring using the hybrid neural discriminant technique (2002)Credit scoring using the hybr…Neural network credit scoring models (2000)Neural network credit scoring…A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)A survey of credit and behavi…Financial credit-risk evaluation with neural and neurofuzzy systems (1999)Financial credit-risk evaluat…Multivariate Normality and Forecasting of Business Bankruptcy (1987)Multivariate Normality and Fo…An Examination of the Conceptual Issues Involved in Developing Credit-Scoring Models (1983)An Examination of the Concept…Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods (2023)Consumer credit risk assessme…A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain (2022)A novel ensemble feature sele…Experimental analysis of machine learning methods for credit score classification (2021)Experimental analysis of mach…Credit Scoring Models Using Ensemble Learning and Classification Approaches: A Comprehensive Survey (2021)Credit Scoring Models Using E…Supply chain finance credit risk assessment using support vector machine–based ensemble improved with noise elimination (2020)Supply chain finance credit r…A novel hybrid credit scoring model based on ensemble feature selection and multilayer ensemble classification (2019)A novel hybrid credit scoring…Stationary Mahalanobis kernel SVM for credit risk evaluation (2018)Stationary Mahalanobis kernel…Hybrid credit scoring model using neighborhood rough set and multi-layer ensemble classification (2018)Hybrid credit scoring model u…Credit Scoring Model based on Weighted Voting and Cluster based Feature Selection (2018)Credit Scoring Model based on…An Efficient Multi-layer Ensemble Framework with BPSOGSA-Based Feature Selection for Credit Scoring Data Analysis (2017)An Efficient Multi-layer Ense…Using data mining and neural networks techniques to propose a new hybrid customer behaviour analysis and credit scoring model in banking services based on a developed RFM analysis method (2016)Using data mining and neural …Classification methods applied to credit scoring: Systematic review and overall comparison (2016)Classification methods applie…Application of a rule extraction algorithm family based on the Re-RX algorithm to financial credit risk assessment from a Pareto optimal perspective (2016)Application of a rule extract…An insight into the experimental design for credit risk and corporate bankruptcy prediction systems (2014)An insight into the experimen…Credit scoring in banks and financial institutions via data mining techniques: A literature review (2013)Credit scoring in banks and f…Balancing accuracy, complexity and interpretability in consumer credit decision making: A C-TOPSIS classification approach (2013)Balancing accuracy, complexit…The Pricing of Options and Corporate Liabilities (1973)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)Credit scoring with a data mining approach based on support vector machines (2006)Recent developments in consumer credit risk assessment (2007)A comparative assessment of ensemble learning for credit scoring (2010)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Forecasting with artificial neural networks: (1998)Building credit scoring models using genetic programming (2005)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)Machine Learning in Financial Crisis Prediction: A Survey (2011)Neural Networks: A New Tool for Predicting Thrift Failures* (1992)An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring (2007)Credit rating by hybrid machine learning techniques (2009)Financial Ratios As Predictors of Failure (1966)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Qualitative Response Models: A Survey (1994)Hybrid neural network models for bankruptcy predictions (1996)Portfolio selection and skewness: Evidence from international stock markets (1997)The value of non-financial information in SME risk management (2010)Information Choice and Utilization in an Experiment on Default Prediction (1980)A fuzzy neural network for assessing the risk of fraudulent financial reporting (2003)Credit scoring models for the microfinance industry using neural networks: Evidence from Peru (2012)Bankruptcy visualization and prediction using neural networks: A study of U.S. commercial banks (2014)Foundations of Finance: Portfolio Decisions and Securities Prices (1978)A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior (1980)A practical approach to credit scoring (2007)Mining the customer credit using hybrid support vector machine technique (2008)Computational time reduction for credit scoring: An integrated approach based on support vector machine and stratified sampling method (2012)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends (2019)The influence of enterprise risk management on firm performance with the moderating effect of intellectual capital dimensions (2020)Credit scoring methods: Latest trends and points to consider (2022)Financial time series forecasting using support vector machines (2003)Integrating data augmentation and hybrid feature selection for small sample credit risk assessment with high dimensionality (2022)Credit scoring prediction leveraging interpretable ensemble learning (2023)Prioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework (2023)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)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)
this work references cited by second hop

References

  • 2000Neural network credit scoring models1,032 cited
  • 2000A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers744 cited
  • 2002Credit scoring using the hybrid neural discriminant technique355 cited
  • 1987Multivariate Normality and Forecasting of Business Bankruptcy354 cited
  • 1999Financial credit-risk evaluation with neural and neurofuzzy systems236 cited
  • 2003Credit scoring and rejected instances reassigning through evolutionary computation techniques226 cited
  • 2005Hybrid mining approach in the design of credit scoring models196 cited
  • 1983An Examination of the Conceptual Issues Involved in Developing Credit-Scoring Models137 cited

Cited by

  • 2022A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain95 cited
  • 2014An insight into the experimental design for credit risk and corporate bankruptcy prediction systems75 cited
  • 2019A novel hybrid credit scoring model based on ensemble feature selection and multilayer ensemble classification73 cited
  • 2023Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods71 cited
  • 2016Classification methods applied to credit scoring: Systematic review and overall comparison68 cited

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  • 2013Balancing accuracy, complexity and interpretability in consumer credit decision making: A C-TOPSIS classification approach62 cited
  • 2018Hybrid credit scoring model using neighborhood rough set and multi-layer ensemble classification59 cited
  • 2018Credit Scoring Model based on Weighted Voting and Cluster based Feature Selection53 cited
  • 2018Stationary Mahalanobis kernel SVM for credit risk evaluation49 cited
  • 2017An Efficient Multi-layer Ensemble Framework with BPSOGSA-Based Feature Selection for Credit Scoring Data Analysis48 cited
  • 2020Supply chain finance credit risk assessment using support vector machine–based ensemble improved with noise elimination44 cited
  • 2013Credit scoring in banks and financial institutions via data mining techniques: A literature review42 cited
  • 2016Application of a rule extraction algorithm family based on the Re-RX algorithm to financial credit risk assessment from a Pareto optimal perspective39 cited
  • 2021Experimental analysis of machine learning methods for credit score classification38 cited
  • 2021Credit Scoring Models Using Ensemble Learning and Classification Approaches: A Comprehensive Survey38 cited
  • 2016Using data mining and neural networks techniques to propose a new hybrid customer behaviour analysis and credit scoring model in banking services based on a developed RFM analysis method35 cited