Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Foundations of Soft Case-Based Reasoning
Foundations of Soft Case-Based Reasoning
Case-Based Reasoning: Concepts, Features and Soft Computing
Applied Intelligence
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Bounds on Error Expectation for Support Vector Machines
Neural Computation
Soft computing system for bank performance prediction
Applied Soft Computing
Short communication: Data mining method for listed companies' financial distress prediction
Knowledge-Based Systems
A rough margin based support vector machine
Information Sciences: an International Journal
Two stages of case-based reasoning - Integrating genetic algorithm with data mining mechanism
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
On-line fuzzy modeling via clustering and support vector machines
Information Sciences: an International Journal
A hierarchical design of case-based reasoning in the balanced scorecard application
Expert Systems with Applications: An International Journal
Financial distress early warning based on group decision making
Computers and Operations Research
Zero anaphora resolution by case-based reasoning and pattern conceptualization
Expert Systems with Applications: An International Journal
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
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
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Case-based reasoning (CBR) is a machine learning technique of high performance in classification problems, and it is also a chief method in predicting business failure. Recently, several techniques have been introduced into the life-cycle of CBR for business failure prediction (BFP). The drawback of former researches on CBR-based BFP is that they only use total predictive accuracy when assessing CBR. In this research, we provide evidence on performance of CBR in Chinese BFP from various views of sensitivity, specificity, positive and negative values. Data are collected from Shanghai Stock Exchange and Shenzhen Stock Exchange in China. And we present how data are preprocessed from the view of data mining. The classical CBR model on the base of Euclidean metric, the grey CBR model on the base of grey coefficient metric, and the pseudo CBR model on the base of pseudo outranking relations are employed to make a comparative study on CBR's predictive performance in BFP. Meanwhile, support vector machine (SVM) is employed to be a baseline model for comparison. The results indicate that pseudo CBR produces better performance in Chinese BFP than classical CBR and grey CBR significantly on the whole, and it outperforms SVM marginally by total predictive accuracy and sensitivity, while it is not significantly worse than SVM by specificity.