Bankruptcy prediction using neural networks
Decision Support Systems - Special issue on neural networks for decision support
Machine Learning
Hybrid neural network models for bankruptcy predictions
Decision Support Systems
Using Feature Construction to Improve the Performance of Neural Networks
Management Science
Genetically Optimized Neural Network Classifiers for Bankruptcy Prediction- An Empirical Study
HICSS '96 Proceedings of the 29th Hawaii International Conference on System Sciences Volume 2: Decision Support and Knowledge-Based Systems
Application of Feature Extractive Algorithm to Bankruptcy Prediction
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
Selecting Bankruptcy Predictors Using a Support Vector Machine Approach
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Choosing Bankruptcy Predictors Using Discriminant Analysis, Logit Analysis, and Genetic Algorithms
Choosing Bankruptcy Predictors Using Discriminant Analysis, Logit Analysis, and Genetic Algorithms
Machine Learning
Neural network ensemble strategies for financial decision applications
Computers and Operations Research
Computers and Operations Research
Journal of Management Information Systems - Special section: Data mining
Analysing company performance using templates
Intelligent Data Analysis
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks
Decision Support Systems
Expert Systems with Applications: An International Journal
Application of HLVQ and G-Prop Neural Networks to the Problem of Bankruptcy Prediction
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms
Expert Systems with Applications: An International Journal
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
Bankruptcy prediction for credit risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks
Editorial: European Symposium on Times Series Prediction
Neurocomputing
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Bankruptcy trajectory analysis on french companies using self-organizing map
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
Clustering and visualization of bankruptcy trajectory using self-organizing map
Expert Systems with Applications: An International Journal
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We evaluate the prediction accuracy of models designed using different classification methods depending on the technique used to select variables, and we study the relationship between the structure of the models and their ability to correctly predict financial failure. We show that a neural network based model using a set of variables selected with a criterion that it is adapted to the network leads to better results than a set chosen with criteria used in the financial literature. We also show that the way in which a set of variables may represent the financial profiles of healthy companies plays a role in Type I error reduction.