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Dynamic weighted ensemble classification for credit scoring using Markov Chain
16 references·8 citing·33 second hop
Dynamic weighted ensemble classification for credit scoring using Markov Chain (2018)Dynamic weighted ensemble classification …Ensemble classification based on supervised clustering for credit scoring (2016)Ensemble classification based…Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble (2016)Dynamic financial distress pr…Classifiers consensus system approach for credit scoring (2016)Classifiers consensus system …Financial credit risk assessment: a recent review (2015)Financial credit risk assessm…Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Benchmarking state-of-the-art…Improving experimental studies about ensembles of classifiers for bankruptcy prediction and credit scoring (2013)Improving experimental studie…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…Machine Learning in Financial Crisis Prediction: A Survey (2011)Machine Learning in Financial…Credit rating by hybrid machine learning techniques (2009)Credit rating by hybrid machi…The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)The comparisons of data minin…Recent developments in consumer credit risk assessment (2007)Recent developments in consum…Neural nets versus conventional techniques in credit scoring in Egyptian banking (2007)Neural nets versus convention…Credit Scoring and Its Applications (2002)Credit Scoring and Its Applic…Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Statistical Classification Me…A Markov Model for the Term Structure of Credit Risk Spreads (1997)A Markov Model for the Term S…CATE: Contrastive augmentation and tree-enhanced embedding for credit scoring (2023)CATE: Contrastive augmentatio…Tree-based heterogeneous cascade ensemble model for credit scoring (2022)Tree-based heterogeneous casc…Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence (2022)Review of Multi-Criteria Deci…Novel hybrid ensemble credit scoring model with stacking-based noise detection and weight assignment (2022)Novel hybrid ensemble credit …Deep learning meets decision trees: An application of a heterogeneous deep forest approach in credit scoring for online consumer lending (2022)Deep learning meets decision …Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach (2021)Forecasting loss given defaul…Machine learning predictivity applied to consumer creditworthiness (2020)Machine learning predictivity…Forecasting Financial Distress With Machine Learning – A Review (2020)Forecasting Financial Distres…Fuzzy sets (1965)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Fuzzy sets (1996)Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring (2019)Deep learning for credit scoring: Do or don’t? (2021)Operational Research and Artificial Intelligence Methods in Banking (2022)The Pricing of Options and Corporate Liabilities (1973)Neural network credit scoring models (2000)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)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Machine Learning in Banking Risk Management: A Literature Review (2019)A Review on Fairness in Machine Learning (2022)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Forecasting bank failures and stress testing: A machine learning approach (2018)Integration of unsupervised and supervised machine learning algorithms for credit risk assessment (2019)Multi-class misclassification cost matrix for credit ratings in peer-to-peer lending (2020)Forecasting with artificial neural networks: (1998)The effect of feature selection on financial distress prediction (2014)A hybrid ETS–ANN model for time series forecasting (2017)ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES* (1974)A Theory of the Term Structure of Interest Rates (1985)Arbitrage Theory in Continuous Time (1998)Explaining the Rate Spread on Corporate Bonds (2001)Term Structures of Credit Spreads with Incomplete Accounting Information (2001)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects (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)Consumer credit-risk models via machine-learning algorithms (2010)Two-stage consumer credit risk modelling using heterogeneous ensemble learning (2019)Big data, artificial intelligence and machine learning: A transformative symbiosis in favour of financial technology (2022)
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References

  • 1997A Markov Model for the Term Structure of Credit Risk Spreads1,476 cited
  • 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research1,277 cited
  • 1997Statistical Classification Methods in Consumer Credit Scoring: A Review1,039 cited
  • 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients881 cited
  • 2002Credit Scoring and Its Applications669 cited
  • 2007Recent developments in consumer credit risk assessment472 cited
  • 2011Machine Learning in Financial Crisis Prediction: A Survey325 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 data241 cited
  • 2015Financial credit risk assessment: a recent review234 cited
  • 2016Classifiers consensus system approach for credit scoring202 cited
  • 2009Credit rating by hybrid machine learning techniques177 cited
  • 2016Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble173 cited
  • 2007Neural nets versus conventional techniques in credit scoring in Egyptian banking168 cited
  • 2016Ensemble classification based on supervised clustering for credit scoring

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160 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
  • Cited by

    • 2022Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence76 cited
    • 2021Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach42 cited
    • 2022Tree-based heterogeneous cascade ensemble model for credit scoring40 cited
    • 2022Novel hybrid ensemble credit scoring model with stacking-based noise detection and weight assignment40 cited
    • 2020Machine learning predictivity applied to consumer creditworthiness39 cited
    • 2022Deep learning meets decision trees: An application of a heterogeneous deep forest approach in credit scoring for online consumer lending18 cited
    • 2020Forecasting Financial Distress With Machine Learning – A Review15 cited
    • 2023CATE: Contrastive augmentation and tree-enhanced embedding for credit scoring13 cited