International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
The Strength of Weak Learnability
Machine Learning
Machine Learning
Knowledge Acquisition From Multiple Experts: An Empirical Study
Management Science
Boosting regression estimators
Neural Computation
Prediction games and arcing algorithms
Neural Computation
Neural networks in business: techniques and applications for the operations researcher
Computers and Operations Research - Neural networks in business
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Computation
Lung cancer cell identification based on artificial neural network ensembles
Artificial Intelligence in Medicine
Stability problems with artificial neural networks and the ensemble solution
Artificial Intelligence in Medicine
A threshold varying bisection method for cost sensitive learning in neural networks
Expert Systems with Applications: An International Journal
Using neural network ensembles for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
A hybrid financial analysis model for business failure prediction
Expert Systems with Applications: An International Journal
Predicting software reliability with neural network ensembles
Expert Systems with Applications: An International Journal
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Diversity of ability and cognitive style for group decision processes
Information Sciences: an International Journal
A selective ensemble based on expected probabilities for bankruptcy prediction
Expert Systems with Applications: An International Journal
A Data Driven Ensemble Classifier for Credit Scoring Analysis
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Business failure prediction using hybrid2 case-based reasoning (H2CBR)
Computers and Operations Research
A data driven ensemble classifier for credit scoring analysis
Expert Systems with Applications: An International Journal
Integration of heterogeneous models to predict consumer behavior
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
The evaluation of consumer loans using support vector machines
Expert Systems with Applications: An International Journal
An ensemble of neural networks for stock trading decision making
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Expert Systems with Applications: An International Journal
Behavioral assessment of recoverable credit of retailer's customers
Information Sciences: an International Journal
Vertical bagging decision trees model for credit scoring
Expert Systems with Applications: An International Journal
Enhancing the classification accuracy by scatter-search-based ensemble approach
Applied Soft Computing
Dynamic financial distress prediction using instance selection for the disposal of concept drift
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Business intelligence for delinquency risk management via cox regression
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
Predicting stock returns by classifier ensembles
Applied Soft Computing
Design of ensemble neural network using entropy theory
Advances in Engineering Software
Principal component case-based reasoning ensemble for business failure prediction
Information and Management
Credit risk evaluation using neural networks: Emotional versus conventional models
Applied Soft Computing
Expert Systems with Applications: An International Journal
Comparative analysis of data mining methods for bankruptcy prediction
Decision Support Systems
A hybrid device for the solution of sampling bias problems in the forecasting of firms' bankruptcy
Expert Systems with Applications: An International Journal
Application of polynomial projection ensembles to hedging crude oil commodity risk
Expert Systems with Applications: An International Journal
Exploring the behaviour of base classifiers in credit scoring ensembles
Expert Systems with Applications: An International Journal
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Two-level classifier ensembles for credit risk assessment
Expert Systems with Applications: An International Journal
Using genetic algorithm based knowledge refinement model for dividend policy forecasting
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Application of hybrid case-based reasoning for enhanced performance in bankruptcy prediction
Information Sciences: an International Journal
Empirical study of bagging predictors on medical data
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Predicting the helpfulness of online reviews using multilayer perceptron neural networks
Expert Systems with Applications: An International Journal
Machine learning-based classifiers ensemble for credit risk assessment
International Journal of Electronic Finance
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Considerable research effort has been expended to identify more accurate models for decision support systems in financial decision domains including credit scoring and bankruptcy prediction. The focus of this earlier work has been to identify the "single best" prediction model from a collection that includes simple parametric models, nonparametric models that directly estimate data densities, and nonlinear pattern recognition models such as neural networks. Recent theories suggest this work may be misguided in that ensembles of predictors provide more accurate generalization than the reliance on a single model. This paper investigates three recent ensemble strategies: crossvalidation, bagging, and boosting. We employ the multilayer perceptron neural network as a base classifier. The generalization ability of the neural network ensemble is found to be superior to the single best model for three real world financial decision applications.