IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural network applications in finance: a review and analysis of literature (1990-1996)
Information and Management
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
Multiclassifier Systems: Back to the Future
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
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
Evaluation of the Information-Theoretic Construction of Multiple Classifier Systems
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Neural network ensemble strategies for financial decision applications
Computers and Operations Research
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Computational Statistics & Data Analysis
Building credit scoring models using genetic programming
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
Gaussian case-based reasoning for business failure prediction with empirical data in China
Information Sciences: an International Journal
Majority voting combination of multiple case-based reasoning for financial distress prediction
Expert Systems with Applications: An International Journal
Feature selection in bankruptcy prediction
Knowledge-Based Systems
Financial distress prediction based on serial combination of multiple classifiers
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
Genetic programming for credit scoring: The case of Egyptian public sector banks
Expert Systems with Applications: An International Journal
Business failure prediction using hybrid2 case-based reasoning (H2CBR)
Computers and Operations Research
Expert Systems with Applications: An International Journal
A data driven ensemble classifier for credit scoring analysis
Expert Systems with Applications: An International Journal
Development of a quick credibility scoring decision support system using fuzzy TOPSIS
Expert Systems with Applications: An International Journal
Integration of heterogeneous models to predict consumer behavior
Expert Systems with Applications: An International Journal
Integrating web mining and neural network for personalized e-commerce automatic service
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Enhancing the classification accuracy by scatter-search-based ensemble approach
Applied Soft Computing
Understanding consumer heterogeneity: A business intelligence application of neural networks
Knowledge-Based Systems
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
Predicting business failure using forward ranking-order case-based reasoning
Expert Systems with Applications: An International Journal
The parameters effect on performance in ANN for hand gesture recognition system
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
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Principal component case-based reasoning ensemble for business failure prediction
Information and Management
Financial time series forecast using neural network ensembles
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
A hybrid model for credit evaluation problem
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
Credit risk evaluation using neural networks: Emotional versus conventional models
Applied Soft Computing
Expert Systems with Applications: An International Journal
An application of locally linear model tree algorithm for predictive accuracy of credit scoring
MEDI'11 Proceedings of the First international conference on Model and data engineering
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A hybrid ensemble approach for enterprise credit risk assessment based on Support Vector Machine
Expert Systems with Applications: An International Journal
Simple instance selection for bankruptcy prediction
Knowledge-Based Systems
A hybrid device for the solution of sampling bias problems in the forecasting of firms' bankruptcy
Expert Systems with Applications: An International Journal
Fuzzy type 2 inference system for credit scoring
ACMOS'09 Proceedings of the 11th WSEAS international conference on Automatic control, modelling and simulation
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Determinants of intangible assets value: The data mining approach
Knowledge-Based Systems
An overview of the use of neural networks for data mining tasks
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
DRFLogitBoost: a double randomized decision forest incorporated with logitboosted decision stumps
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Financial distress prediction using support vector machines: Ensemble vs. individual
Applied Soft Computing
Using genetic algorithm based knowledge refinement model for dividend policy forecasting
Expert Systems with Applications: An International Journal
Empirical models based on features ranking techniques for corporate financial distress prediction
Computers & Mathematics with Applications
A neural network approach to predicting price negotiation outcomes in business-to-business contexts
Expert Systems with Applications: An International Journal
Assessing scorecard performance: A literature review and classification
Expert Systems with Applications: An International Journal
Novel feature selection methods to financial distress prediction
Expert Systems with Applications: An International Journal
An improved boosting based on feature selection for corporate bankruptcy prediction
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.09 |
Bankruptcy prediction and credit scoring have long been regarded as critical topics and have been studied extensively in the accounting and finance literature. Artificial intelligence and machine learning techniques have been used to solve these financial decision-making problems. The multilayer perceptron (MLP) network trained by the back-propagation learning algorithm is the mostly used technique for financial decision-making problems. In addition, it is usually superior to other traditional statistical models. Recent studies suggest combining multiple classifiers (or classifier ensembles) should be better than single classifiers. However, the performance of multiple classifiers in bankruptcy prediction and credit scoring is not fully understood. In this paper, we investigate the performance of a single classifier as the baseline classifier to compare with multiple classifiers and diversified multiple classifiers by using neural networks based on three datasets. By comparing with the single classifier as the benchmark in terms of average prediction accuracy, the multiple classifiers only perform better in one of the three datasets. The diversified multiple classifiers trained by not only different classifier parameters but also different sets of training data perform worse in all datasets. However, for the Type I and Type II errors, there is no exact winner. We suggest that it is better to consider these three classifier architectures to make the optimal financial decision.