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A Novel Noise-Adapted Two-Layer Ensemble Model for Credit Scoring Based on Backflow Learning
16 references·5 citing·34 second hop
A Novel Noise-Adapted Two-Layer Ensemble Model for Credit Scoring Based on Backflow Learning (2019)A Novel Noise-Adapted Two-Layer Ensemble …A novel multi-stage hybrid model with enhanced multi-population niche genetic algorithm: An application in credit scoring (2018)A novel multi-stage hybrid mo…A novel heterogeneous ensemble credit scoring model based on bstacking approach (2017)A novel heterogeneous ensembl…Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)Ensemble boosted trees with s…Classifiers consensus system approach for credit scoring (2016)Classifiers consensus system …A two-stage classification technique for bankruptcy prediction (2016)A two-stage classification te…Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Benchmarking state-of-the-art…The effect of feature selection on financial distress prediction (2014)The effect of feature selecti…Bankruptcy prediction for Russian companies: Application of combined classifiers (2013)Bankruptcy prediction for Rus…Machine Learning in Financial Crisis Prediction: A Survey (2011)Machine Learning in Financial…A comparative assessment of ensemble learning for credit scoring (2010)A comparative assessment of e…An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring (2008)An experimental comparison of…Recent developments in consumer credit risk assessment (2007)Recent developments in consum…Neural network ensemble strategies for financial decision applications (2004)Neural network ensemble strat…Mining the customer credit using classification and regression tree and multivariate adaptive regression splines (2004)Mining the customer credit us…Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Credit rating analysis with s…Machine-learning algorithms for credit-card applications (1992)Machine-learning algorithms f…Enhancing credit scoring accuracy with a comprehensive evaluation of alternative data (2024)Enhancing credit scoring accu…Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset (2024)Advancing Bankruptcy Forecast…Two-stage credit scoring using Bayesian approach (2022)Two-stage credit scoring usin…Improved credit scoring model using XGBoost with Bayesian hyper-parameter optimization (2021)Improved credit scoring model…A Novel GSCI-Based Ensemble Approach for Credit Scoring (2020)A Novel GSCI-Based Ensemble A…Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Neural network credit scoring models (2000)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)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)Financial credit risk assessment: a recent review (2015)A comparative study on base classifiers in ensemble methods for credit scoring (2016)What's In A Name? Malay Seals As Onomastic Sources (2018)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)Comparative analysis of data mining methods for bankruptcy prediction (2011)The Pricing of Options and Corporate Liabilities (1973)CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE (2011)A review of trade credit literature: Opportunities for research in operations (2013)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems (2005)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring (2015)Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering (2022)A Discriminant Analysis of Predictors of Business Failure (1972)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Credit scoring with a data mining approach based on support vector machines (2006)Consumer credit-risk models via machine-learning algorithms (2010)Forecasting with artificial neural networks: (1998)A hybrid ETS–ANN model for time series forecasting (2017)Financial Ratios As Predictors of Failure (1966)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Predicting failure in the U.S. banking sector: An extreme gradient boosting approach (2018)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)'It's Reducing a Human Being to a Percentage' (2018)Machine Learning and Natural Language Processing in Mental Health: Systematic Review (2020)Computer assisted customer churn management: State-of-the-art and future trends (2005)
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References

  • 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research1,277 cited
  • 2003Credit rating analysis with support vector machines and neural networks: a market comparative study1,017 cited
  • 2010A comparative assessment of ensemble learning for credit scoring501 cited
  • 2007Recent developments in consumer credit risk assessment472 cited
  • 2016Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction419 cited
  • 2004Mining the customer credit using classification and regression tree and multivariate adaptive regression splines378 cited
  • 2004Neural network ensemble strategies for financial decision applications332 cited
  • 2011Machine Learning in Financial Crisis Prediction: A Survey325 cited
  • 2008An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring290 cited
  • 2014The effect of feature selection on financial distress prediction234 cited
  • 2017A novel heterogeneous ensemble credit scoring model based on bstacking approach214 cited
  • 2016Classifiers consensus system approach for credit scoring202 cited
  • 2016A two-stage classification technique for bankruptcy prediction142 cited
  • 2018A novel multi-stage hybrid model with enhanced multi-population niche genetic algorithm: An application in credit scoring

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139 cited
  • 1992Machine-learning algorithms for credit-card applications128 cited
  • 2013Bankruptcy prediction for Russian companies: Application of combined classifiers90 cited
  • Cited by

    • 2024Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset32 cited
    • 2024Enhancing credit scoring accuracy with a comprehensive evaluation of alternative data27 cited
    • 2020A Novel GSCI-Based Ensemble Approach for Credit Scoring24 cited
    • 2021Improved credit scoring model using XGBoost with Bayesian hyper-parameter optimization20 cited
    • 2022Two-stage credit scoring using Bayesian approach19 cited