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Combination of Feature Selection and Optimized Fuzzy Apriori Rules: The Case of Credit Scoring
16 references·1 citing·30 second hop
Combination of Feature Selection and Optimized Fuzzy Apriori Rules: The Case of Credit Scoring (2015)Combination of Feature Selection and Opti…A comparative assessment of ensemble learning for credit scoring (2010)A comparative assessment of e…Combination of feature selection approaches with SVM in credit scoring (2009)Combination of feature select…An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring (2008)An experimental comparison of…Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Using neural network ensemble…Recent developments in consumer credit risk assessment (2007)Recent developments in consum…Credit scoring with a data mining approach based on support vector machines (2006)Credit scoring with a data mi…Application of support vector machines to corporate credit rating prediction (2006)Application of support vector…Hybrid mining approach in the design of credit scoring models (2005)Hybrid mining approach in the…Building credit scoring models using genetic programming (2005)Building credit scoring model…A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines (2005)A two-stage hybrid credit sco…Neural network ensemble strategies for financial decision applications (2004)Neural network ensemble strat…Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Credit rating analysis with s…Differentiating between good credits and bad credits using neuro-fuzzy systems (2002)Differentiating between good …Credit scoring using the hybrid neural discriminant technique (2002)Credit scoring using the hybr…Neural network credit scoring models (2000)Neural network credit scoring…Thirteen Ways to Look at the Correlation Coefficient (1988)Thirteen Ways to Look at the …Feature selection based on machine learning for credit scoring : An evaluation of filter and embedded methods (2021)Feature selection based on ma…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)A Discriminant Analysis of Predictors of Business Failure (1972)Forecasting with artificial neural networks: (1998)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)An empirical comparison of conventional techniques, neural networks and the three stage hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) model for credit scoring analysis: The case of Turkish credit card data (2012)A comparative study on base classifiers in ensemble methods for credit scoring (2016)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Machine Learning in Financial Crisis Prediction: A Survey (2011)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)The Pricing of Options and Corporate Liabilities (1973)A review of trade credit literature: Opportunities for research in operations (2013)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Consumer credit-risk models via machine-learning algorithms (2010)Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) (1994)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Statistical Theories of Mental Test Scores (1969)The Foundations of Factor Analysis. (1975)The Essential Guide to Effect Sizes (2010)Educational measurement. (2015)Textual Analysis in Accounting and Finance: A Survey (2016)Correlation Coefficients: Appropriate Use and Interpretation (2018)A comparison of neural networks and linear scoring models in the credit union environment (1996)Business failure prediction using rough sets (1999)Forecasting energy consumption using a grey model improved by incorporating genetic programming (2010)Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities (2015)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis (2021)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Machine behaviour (2019)
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References

  • 1988Thirteen Ways to Look at the Correlation Coefficient4,068 cited
  • 2000Neural network credit scoring models1,032 cited
  • 2003Credit rating analysis with support vector machines and neural networks: a market comparative study1,017 cited
  • 2006Credit scoring with a data mining approach based on support vector machines805 cited
  • 2007Using neural network ensembles for bankruptcy prediction and credit scoring514 cited
  • 2010A comparative assessment of ensemble learning for credit scoring501 cited
  • 2007Recent developments in consumer credit risk assessment472 cited
  • 2005A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines389 cited
  • 2005Building credit scoring models using genetic programming356 cited
  • 2002Credit scoring using the hybrid neural discriminant technique355 cited
  • 2004Neural network ensemble strategies for financial decision applications332 cited
  • 2008An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring290 cited
  • 2002Differentiating between good credits and bad credits using neuro-fuzzy systems252 cited
  • 2006Application of support vector machines to corporate credit rating prediction205 cited

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2009
Combination of feature selection approaches with SVM in credit scoring
202 cited
  • 2005Hybrid mining approach in the design of credit scoring models196 cited
  • Cited by

    • 2021Feature selection based on machine learning for credit scoring : An evaluation of filter and embedded methods20 cited