Forecasting with neural networks
Information and Management
Self organizing neural networks for financial diagnosis
Decision Support Systems
Combination of multiple classifiers for the customer's purchase behavior prediction
Decision Support Systems - Special issue: Agents and e-commerce business models
A New Rough Set Approach to Multicriteria and Multiattribute Classification
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Computers and Operations Research
Expert Systems with Applications: An International Journal
Using neural network ensembles for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Forecasting financial condition of Chinese listed companies based on support vector machine
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An integrative model with subject weight based on neural network learning for bankruptcy prediction
Expert Systems with Applications: An International Journal
Financial distress prediction based on OR-CBR in the principle of k-nearest neighbors
Expert Systems with Applications: An International Journal
Financial distress early warning based on group decision making
Computers and Operations Research
Ranking-order case-based reasoning for financial distress prediction
Knowledge-Based Systems
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Financial distress prediction based on similarity weighted voting CBR
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
An application of support vector machine to companies' financial distress prediction
MDAI'06 Proceedings of the Third international conference on Modeling Decisions for Artificial Intelligence
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A multi-agent system for web-based risk management in small and medium business
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Serial combination of multiple classifiers for automatic blue whale calls recognition
Expert Systems with Applications: An International Journal
Novel feature selection methods to financial distress prediction
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Financial distress is the most synthetic form of business crisis and financial distress prediction (FDP) has been a widely and continually studied topic in the field of corporate finance. Recently, the advantage of FDP based on multiple classifiers' combination began to be emphasized. This paper attempts to put forward a FDP method based on serial combination of multiple classifiers, which tries to make use of class-wise expertise of diverse base classifiers in serial combination system. Framework of serial combination system for FDP, selection mechanism of base classifiers and algorithm of FDP based on serial combination are discussed in detail. With financial condition dividing into two categories, empirical experiment indicated that FDP method based on serial combination of multiple classifiers performs at least as well as the best base classifier in average accuracy and stability, but it did not show much advantage in information complementation from base classifiers and was easy to be dominated by the first base classifier in serial combination system. This may be attributed to the number of target categories and serial combination method was inferred to be more suitable for FDP with multiple categories, which leaves to be further studied.