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A Discretized Enriched Technique to Enhance Machine Learning Performance in Credit Scoring
16 references·1 citing·46 second hop
A Discretized Enriched Technique to Enhance Machine Learning Performance in Credit Scoring (2019)A Discretized Enriched Technique to Enhan…Hybrid credit scoring model using neighborhood rough set and multi-layer ensemble classification (2018)Hybrid credit scoring model u…Credit risk assessment for unbalanced datasets based on data mining, artificial neural network and support vector machines (2018)Credit risk assessment for un…Machine learning models and bankruptcy prediction (2017)Machine learning models and b…A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)A boosted decision tree appro…Technology credit scoring model with fuzzy logistic regression (2016)Technology credit scoring mod…Intelligent Credit Scoring (2016)Intelligent Credit ScoringBig data preprocessing: methods and prospects (2016)Big data preprocessing: metho…A deep learning approach for credit scoring using credit default swaps (2016)A deep learning approach for …Risk assessment in social lending via random forests (2015)Risk assessment in social len…RECENT DEVELOPMENTS IN CONSUMER CREDIT AND DEFAULT LITERATURE (2015)RECENT DEVELOPMENTS IN CONSUM…Financial credit risk assessment: a recent review (2015)Financial credit risk assessm…Credit scoring using the clustered support vector machine (2014)Credit scoring using the clus…A Hybrid Support Vector Machine Ensemble Model for Credit Scoring (2011)A Hybrid Support Vector Machi…Recent developments in consumer credit risk assessment (2007)Recent developments in consum…In-sample vs. out-of-sample tests of stock return predictability in the context of data mining (2005)In-sample vs. out-of-sample t…What's the point of credit scoring? (1997)What's the point of credit sc…A Gaussian process‐based approach toward credit risk modeling using stationary activations (2021)A Gaussian process‐based appr…Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) (1994)Credit risk measurement: Developments over the last 20 years (1997)Does Distance Still Matter? 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(2005)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Natural language based financial forecasting: a survey (2017)Machine Learning in Banking Risk Management: A Literature Review (2019)Deep learning for financial applications : A survey (2020)Factor Analysis (1978)2013 IEEE International Conference on Big Data (2013)Data mining with big data (2013)Big Data Quality: A Survey (2018)Big data monetization throughout Big Data Value Chain: a comprehensive review (2020)Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering (2022)Support vector machines for credit scoring and discovery of significant features (2008)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda (2022)Machine learning-driven credit risk: a systemic review (2022)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)Forecasting gold price with the XGBoost algorithm and SHAP interaction values (2021)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)
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References

  • 2017Machine learning models and bankruptcy prediction952 cited
  • 2017A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring770 cited
  • 2016Big data preprocessing: methods and prospects734 cited
  • 2007Recent developments in consumer credit risk assessment472 cited
  • 2015Risk assessment in social lending via random forests398 cited
  • 1997What's the point of credit scoring?311 cited
  • 2014Credit scoring using the clustered support vector machine269 cited
  • 2005In-sample vs. out-of-sample tests of stock return predictability in the context of data mining257 cited
  • 2015Financial credit risk assessment: a recent review234 cited
  • 2016A deep learning approach for credit scoring using credit default swaps196 cited
  • 2016Technology credit scoring model with fuzzy logistic regression155 cited
  • 2016Intelligent Credit Scoring77 cited
  • 2018Credit risk assessment for unbalanced datasets based on data mining, artificial neural network and support vector machines72 cited
  • 2018Hybrid credit scoring model using neighborhood rough set and multi-layer ensemble classification59 cited
  • 2011A Hybrid Support Vector Machine Ensemble Model for Credit Scoring

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53 cited
  • 2015RECENT DEVELOPMENTS IN CONSUMER CREDIT AND DEFAULT LITERATURE52 cited
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    • 2021A Gaussian process‐based approach toward credit risk modeling using stationary activations11 cited