SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
12 references·16 citing·25 second hop
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring (2008)An experimental comparison of ensemble of…What's In A Name? Malay Seals As Onomastic Sources (2018)What's In A Name? Malay Seals…Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Using neural network ensemble…Building credit scoring models using genetic programming (2005)Building credit scoring model…Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Bankruptcy prediction using s…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…An application of support vector machines in bankruptcy prediction model (2004)An application of support vec…Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Credit rating analysis with s…Credit scoring using the hybrid neural discriminant technique (2002)Credit scoring using the hybr…Bankruptcy prediction for credit risk using neural networks: A survey and new results (2001)Bankruptcy prediction for cre…Neural network credit scoring models (2000)Neural network credit scoring…Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis (1999)Artificial neural networks in…Data analytic approach for bankruptcy prediction (2019)Data analytic approach for ba…Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring (2019)Application of new deep genet…A novel heterogeneous ensemble credit scoring model based on bstacking approach (2017)A novel heterogeneous ensembl…Classifiers consensus system approach for credit scoring (2016)Classifiers consensus system …A new hybrid ensemble credit scoring model based on classifiers consensus system approach (2016)A new hybrid ensemble credit …A comparative study on base classifiers in ensemble methods for credit scoring (2016)A comparative study on base c…Financial credit risk assessment: a recent review (2015)Financial credit risk assessm…A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring (2015)A hybrid data mining model of…A comparative study of classifier ensembles for bankruptcy prediction (2014)A comparative study of classi…Improving experimental studies about ensembles of classifiers for bankruptcy prediction and credit scoring (2013)Improving experimental studie…An improved boosting based on feature selection for corporate bankruptcy prediction (2013)An improved boosting based on…Financial distress prediction using support vector machines: Ensemble vs. individual (2012)Financial distress prediction…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)An empirical comparison of co…A hybrid ensemble approach for enterprise credit risk assessment based on Support Vector Machine (2011)A hybrid ensemble approach fo…Predicting business failure using classification and regression tree: An empirical comparison with popular classical statistical methods and top classification mining methods (2010)Predicting business failure u…Bankruptcy forecasting: A hybrid approach using Fuzzy c-means clustering and Multivariate Adaptive Regression Splines (MARS) (2010)Bankruptcy forecasting: A hyb…Better Decisions through Science (2000)Quality and Complexity Measures for Data Linkage and Deduplication (2007)Do We Know Who Will Drop Out?: A Review of the Predictors of Dropping out of High School: Precision, Sensitivity, and Specificity (2013)Financial Ratios As Predictors of Failure (1966)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review (2020)A Discriminant Analysis of Predictors of Business Failure (1972)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Credit scoring with a data mining approach based on support vector machines (2006)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)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)Machine Learning in Financial Crisis Prediction: A Survey (2011)Forecasting with artificial neural networks: (1998)Computer assisted customer churn management: State-of-the-art and future trends (2005)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE (2011)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)
this work references cited by second hop

References

  • 2018What's In A Name? Malay Seals As Onomastic Sources1,483 cited
  • 2000Neural network credit scoring models1,032 cited
  • 2003Credit rating analysis with support vector machines and neural networks: a market comparative study1,017 cited
  • 2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters872 cited
  • 2004An application of support vector machines in bankruptcy prediction model809 cited
  • 2001Bankruptcy prediction for credit risk using neural networks: A survey and new results696 cited
  • 1999Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis677 cited
  • 2007Using neural network ensembles for bankruptcy prediction and credit scoring514 cited
  • 2004Mining the customer credit using classification and regression tree and multivariate adaptive regression splines378 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

Cited by

  • 2016A comparative study on base classifiers in ensemble methods for credit scoring248 cited
  • 2012An 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

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

241 cited
  • 2015Financial credit risk assessment: a recent review234 cited
  • 2017A novel heterogeneous ensemble credit scoring model based on bstacking approach214 cited
  • 2016Classifiers consensus system approach for credit scoring202 cited
  • 2014A comparative study of classifier ensembles for bankruptcy prediction201 cited
  • 2013An improved boosting based on feature selection for corporate bankruptcy prediction188 cited
  • 2015A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring178 cited
  • 2019Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring176 cited
  • 2010Bankruptcy forecasting: A hybrid approach using Fuzzy c-means clustering and Multivariate Adaptive Regression Splines (MARS)169 cited
  • 2016A new hybrid ensemble credit scoring model based on classifiers consensus system approach161 cited
  • 2011A hybrid ensemble approach for enterprise credit risk assessment based on Support Vector Machine160 cited
  • 2012Financial distress prediction using support vector machines: Ensemble vs. individual153 cited
  • 2013Improving experimental studies about ensembles of classifiers for bankruptcy prediction and credit scoring150 cited
  • 2019Data analytic approach for bankruptcy prediction142 cited
  • 2010Predicting business failure using classification and regression tree: An empirical comparison with popular classical statistical methods and top classification mining methods141 cited