Neural Networks
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Bankruptcy prediction using neural networks
Decision Support Systems - Special issue on neural networks for decision support
The nature of statistical learning theory
The nature of statistical learning theory
Hybrid neural network models for bankruptcy predictions
Decision Support Systems
Hybrid Classifiers for Financial Multicriteria Decision Making: TheCase of Bankruptcy Prediction
Computational Economics
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Self-Organizing Methods in Modeling: Gmdh Type Algorithms
Self-Organizing Methods in Modeling: Gmdh Type Algorithms
Credit Scoring and Its Applications
Credit Scoring and Its Applications
A comparison of machine learning techniques for phishing detection
Proceedings of the anti-phishing working groups 2nd annual eCrime researchers summit
Least squares support vector machines ensemble models for credit scoring
Expert Systems with Applications: An International Journal
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Intelligent phishing detection system for e-banking using fuzzy data mining
Expert Systems with Applications: An International Journal
Assessing the severity of phishing attacks: A hybrid data mining approach
Decision Support Systems
Expert Systems with Applications: An International Journal
Comparative analysis of data mining methods for bankruptcy prediction
Decision Support Systems
Bankruptcy prediction models based on multinorm analysis: An alternative to accounting ratios
Knowledge-Based Systems
Bankruptcy prediction for credit risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks
A general regression neural network
IEEE Transactions on Neural Networks
Clustering and visualization of bankruptcy trajectory using self-organizing map
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Partial Least Square Discriminant Analysis for bankruptcy prediction
Decision Support Systems
Application of hybrid case-based reasoning for enhanced performance in bankruptcy prediction
Information Sciences: an International Journal
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For solving classification and regression problems, we propose a hybrid system consisting of two phases which work in tandem. In the first phase, particle swarm optimization is employed to train a 3-layered auto associative neural network henceforth called PSOAANN. In this phase, dimensionality reduction takes place in hidden layer, where the hidden nodes should be less than the input nodes. The outputs from the hidden nodes are then treated as nonlinear principal components NLPC. They are fed to the second phase where several classifiers and regression methods are invoked. The second phase includes techniques viz., threshold accepting logistic regression TALR, probabilistic neural network PNN, group method of data handling GMDH, support vector machine SVM and genetic programming GP for classification problems. For regression problems, general regression neural network GRNN is used in place of PNN. In addition, support vector machine SVM, Genetic Programming GP, GMDH are also employed, as they are versatile. The efficiency of the hybrid is analyzed on five banking datasets namely Spanish banks, Turkish banks, US banks and UK banks and UK credit dataset and five regression datasets viz., Bodyfat, Forestfires, AutoMPG, Boston Housing and Pollution. All the datasets are analyzed using 10 fold cross validation 10 FCV. It turns out that the proposed hybrid yielded higher accuracies across classification and regression problems.