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A Robust Data‐Mining Approach to Bankruptcy Prediction
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Rough Sets and the role of the monetary policy in financial stability (macroeconomic problem) and the prediction of insolvency in insurance sector (microeconomic problem)
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Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review
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Evaluation of credit risk based on firm performance
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Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
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A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy
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A genetic programming model for bankruptcy prediction: Empirical evidence from Iran
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Differential evolution trained wavelet neural networks: Application to bankruptcy prediction in banks
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Impaired bank health and default risk
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A logistic analysis of bankruptcy within the US local telecommunications industry
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Genetic programming and rough sets: A hybrid approach to bankruptcy classification
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A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction
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Predicting Corporate Financial Distress: A Time-Series CUSUM Methodology
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Nonlinear Genetic-Based Models for Prediction of Flow Number of Asphalt Mixtures
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Predicting corporate failure: empirical evidence for the UK
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Contemporary Studies in Economic and Financial Analysis
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Towards the prediction of business failure via computational intelligence techniques
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ALTERNATIVE MODELS FOR ASSESSING THE FINANCIAL CONDITION OF BUSINESS IN GREECE
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FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY
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Application of Classification Techniques in Business, Banking and Finance.
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Financial Ratios As Predictors of Failure
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Financial Ratios and the Probabilistic Prediction of Bankruptcy
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A Comparison of Several Linear Genetic Programming Techniques
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Gene Expression Programming: a New Adaptive Algorithm for Solving Problems
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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