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Partial dependence analysis of financial ratios in predicting company defaults: random forest vs XGBoost models
11 references·1 citing·48 second hop
Partial dependence analysis of financial ratios in predicting company defaults: random forest vs XGBoost models (2025)Partial dependence analysis of financial …RGA: a unified measure of predictive accuracy (2024)RGA: a unified measure of pre…Predicting financial distress using machine learning approaches: Evidence China (2024)Predicting financial distress…Bank failure prediction models: Review and outlook (2024)Bank failure prediction model…Forecasting nonperforming loans using machine learning (2023)Forecasting nonperforming loa…Revisiting SME default predictors: The Omega Score (2022)Revisiting SME default predic…Deep Learning-Based Model for Financial Distress Prediction (2022)Deep Learning-Based Model for…Application of credit‐scoring methods in a decision support system of investment for peer‐to‐peer lending (2021)Application of credit‐scoring…A Robust Deep Learning Model for Financial Distress Prediction (2020)A Robust Deep Learning Model …Network based credit risk models (2019)Network based credit risk mod…Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey (2019)Evaluating the Performance of…Combining cluster analysis with classifier ensembles to predict financial distress (2011)Combining cluster analysis wi…From Black Box to Clarity: Machine Learning and Agnostic Techniques in Credit Risk Management (2025)From Black Box to Clarity: Ma…Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)A new hybrid ensemble credit scoring model based on classifiers consensus system approach (2016)Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring (2019)EEG-based emotion recognition using tunable Q wavelet transform and rotation forest ensemble classifier (2021)Primary, Secondary, and Meta-Analysis of Research (1976)Financial time series forecasting using support vector machines (2003)Deep learning with long short-term memory networks for financial market predictions (2017)Applications of machine learning for corporate bond yield spread forecasting (2021)Machine Learning Based Explainable Financial Forecasting (2022)The quest for business value drivers: applying machine learning to performance management (2023)A New Status Index Derived from Sociometric Analysis (1953)Financial Contagion (2000)Econometric measures of connectedness and systemic risk in the finance and insurance sectors (2012)COVID-19 pandemic risk and probability of loan default: evidence from marketplace lending market (2021)A systematic review of green finance in the banking industry: perspectives from a developing country (2022)Exploring the impact of green credit policies on corporate financing costs based on the data of Chinese A-share listed companies from 2008 to 2019 (2022)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Prediction of financial distress: An empirical study of listed Chinese companies using data mining (2014)A Comparative Analysis of Machine Learning Classifiers and Ensemble Techniques in Financial Distress Prediction (2020)GALSTM-FDP: A Time-Series Modeling Approach Using Hybrid GA and LSTM for Financial Distress Prediction (2023)Financial distress prediction in emerging markets by using a machine learning approach for financial sustainability (2025)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)RETRACTED: The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China (2023)Artificial Intelligence Techniques for Bankruptcy Prediction of Tunisian Companies: An Application of Machine Learning and Deep Learning-Based Models (2024)Machine learning techniques in bankruptcy prediction: A systematic literature review (2024)Searching for Common Threads: Understanding the Multiple Effects of Diversity in Organizational Groups (1996)DIRECT AND MODERATING EFFECTS OF HUMAN CAPITAL ON STRATEGY AND PERFORMANCE IN PROFESSIONAL SERVICE FIRMS: A RESOURCE-BASED PERSPECTIVE. 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References

  • 2011Combining cluster analysis with classifier ensembles to predict financial distress173 cited
  • 2022Deep Learning-Based Model for Financial Distress Prediction123 cited
  • 2019Network based credit risk models107 cited
  • 2024RGA: a unified measure of predictive accuracy82 cited
  • 2022Revisiting SME default predictors: The Omega Score65 cited
  • 2024Predicting financial distress using machine learning approaches: Evidence China40 cited
  • 2020A Robust Deep Learning Model for Financial Distress Prediction35 cited
  • 2023Forecasting nonperforming loans using machine learning31 cited
  • 2019Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey29 cited
  • 2024Bank failure prediction models: Review and outlook27 cited
  • 2021Application of credit‐scoring methods in a decision support system of investment for peer‐to‐peer lending14 cited

Cited by

  • 2025From Black Box to Clarity: Machine Learning and Agnostic Techniques in Credit Risk Management10 cited

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