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An Automatic Credit Scoring Strategy (ACSS) using memetic evolutionary algorithm and neural architecture search
16 references·0 citing·38 second hop
An Automatic Credit Scoring Strategy (ACSS) using memetic evolutionary algorithm and neural architecture search (2021)An Automatic Credit Scoring Strategy (ACS…Product backorder prediction using deep neural network on imbalanced data (2021)Product backorder prediction …A Profit Function-Maximizing Inventory Backorder Prediction System Using Big Data Analytics (2020)A Profit Function-Maximizing …A new deep learning ensemble credit risk evaluation model with an improved synthetic minority oversampling technique (2020)A new deep learning ensemble …Rule-based credit risk assessment model using multi-objective evolutionary algorithms (2019)Rule-based credit risk assess…Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring (2019)Application of new deep genet…Heterogeneous Ensemble for Default Prediction of Peer-to-Peer Lending in China (2018)Heterogeneous Ensemble for De…A fifty-year retrospective on credit risk models, the Altman Z -score family of models and their applications to financial markets and managerial strategies (2018)A fifty-year retrospective on…Credit default prediction modeling: an application of support vector machine (2017)Credit default prediction mod…A novel heterogeneous ensemble credit scoring model based on bstacking approach (2017)A novel heterogeneous ensembl…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…Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Benchmarking state-of-the-art…A comparative study of classifier ensembles for bankruptcy prediction (2014)A comparative study of classi…Subagging for credit scoring models (2009)Subagging for credit scoring …An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring (2008)An experimental comparison of…Credit risk assessment with a multistage neural network ensemble learning approach (2007)Credit risk assessment with a…ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS (1985)A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)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)Stock market index prediction using artificial neural network (2016)A deep learning ensemble approach for crude oil price forecasting (2017)Credit scoring with a data mining approach based on support vector machines (2006)Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending (2014)A benchmark of machine learning approaches for credit score prediction (2020)Fairness in Machine Learning (2020)What have we learnt from 10 years of fintech research? a scientometric analysis (2020)Neural network credit scoring models (2000)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)Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Bankruptcy visualization and prediction using neural networks: A study of U.S. commercial banks (2014)Ensemble classification based on supervised clustering for credit scoring (2016)Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress (1985)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring (2015)Support vector machines for credit scoring and discovery of significant features (2008)Two-stage consumer credit risk modelling using heterogeneous ensemble learning (2019)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)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring (2019)Integration of unsupervised and supervised machine learning algorithms for credit risk assessment (2019)Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models (2018)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)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 two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network (2022)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)A machine learning approach combining expert knowledge with genetic algorithms in feature selection for credit risk assessment (2021)Credit scoring based on tree-enhanced gradient boosting decision trees (2021)
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References

  • 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research1,277 cited
  • 2015Risk assessment in social lending via random forests398 cited
  • 2007Credit risk assessment with a multistage neural network ensemble learning approach310 cited
  • 2008An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring290 cited
  • 2020A new deep learning ensemble credit risk evaluation model with an improved synthetic minority oversampling technique234 cited
  • 2017A novel heterogeneous ensemble credit scoring model based on bstacking approach214 cited
  • 2009Subagging for credit scoring models213 cited
  • 2014A comparative study of classifier ensembles for bankruptcy prediction201 cited
  • 2016A deep learning approach for credit scoring using credit default swaps196 cited
  • 2019Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring176 cited
  • 2018A fifty-year retrospective on credit risk models, the Altman Z -score family of models and their applications to financial markets and managerial strategies124 cited
  • 2021Product backorder prediction using deep neural network on imbalanced data89 cited
  • 2019Rule-based credit risk assessment model using multi-objective evolutionary algorithms77 cited
  • 2020

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A Profit Function-Maximizing Inventory Backorder Prediction System Using Big Data Analytics
67 cited
  • 2017Credit default prediction modeling: an application of support vector machine65 cited
  • 2018Heterogeneous Ensemble for Default Prediction of Peer-to-Peer Lending in China62 cited
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