C4.5: programs for machine learning
C4.5: programs for machine learning
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
MetaCost: a general method for making classifiers cost-sensitive
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Using analytic QP and sparseness to speed training of support vector machines
Proceedings of the 1998 conference on Advances in neural information processing systems II
Bayesian Models for Early Warning of Bank Failures
Management Science
Bankruptcy prediction by generalized additive models: Research Articles
Applied Stochastic Models in Business and Industry
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks
Decision Support Systems
An integrative model with subject weight based on neural network learning for bankruptcy prediction
Expert Systems with Applications: An International Journal
A selective ensemble based on expected probabilities for bankruptcy prediction
Expert Systems with Applications: An International Journal
The foundations of cost-sensitive learning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms
Expert Systems with Applications: An International Journal
Bankruptcy prediction with neural logic networks by means of grammar-guided genetic programming
Expert Systems with Applications: An International Journal
Using partial least squares and support vector machines for bankruptcy prediction
Expert Systems with Applications: An International Journal
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Comparative analysis of data mining methods for bankruptcy prediction
Decision Support Systems
An improved boosting based on feature selection for corporate bankruptcy prediction
Expert Systems with Applications: An International Journal
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Prediction of corporate bankruptcy is a phenomenon of growing interest to investors, creditors, borrowing firms, and governments alike. Timely identification of firms' impending failure is really wanted. The aim of this research is to use supervised machine learning techniques in such an environment. A number of experiments have been conducted using representative machine learning algorithms, which were trained using a data set of 150 failed and solvent Greek firms. It was found that an ensemble of classifiers could enable users to predict bankruptcies with satisfying precision long before the final bankruptcy.