The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

2013 ◽  
Vol 45 (5) ◽  
pp. 1225-1241 ◽  
Author(s):  
Hui Li ◽  
Jun-Ling Yu ◽  
Le-An Yu ◽  
Jie Sun
Keyword(s):  
Hybrid Approach ◽  
Failure Prediction ◽  
Business Failure ◽  
Case Based Reasoning ◽  
Case Based

Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction

2011 ◽  
Vol 38 (2) ◽  
pp. 409-419 ◽  
Author(s):  
Hui Li ◽  
Hojjat Adeli ◽  
Jie Sun ◽  
Jian-Guang Han
Keyword(s):  
Failure Prediction ◽  
Business Failure ◽  
Case Based Reasoning ◽  
Case Based

Business Failure Prediction: A Case-Based Reasoning Approach

2006 ◽  
Vol 09 (03) ◽  
pp. 491-508 ◽  
Author(s):  
Angela Y. N. Yip
Keyword(s):  
Nearest Neighbor ◽  
Failure Prediction ◽  
Financial Data ◽  
Business Failure ◽  
Similarity Function ◽  
Case Based Reasoning ◽  
Business Failures ◽  
Irrelevant Attributes ◽  
Past Experiences ◽  
Case Based

Case-based reasoning (CBR) is a problem-solving paradigm that uses past experiences to solve new problems. Nearest neighbor is a common CBR algorithm for retrieving similar cases, whose similarity function is sensitive to irrelevant attributes. Taking the relevancy of the attributes into account can reduce this sensitivity, leading to a more effective retrieval of similar cases. In this paper, statistical evaluation is used for assigning relative importance of the attributes. This approach is applied to predict business failures in Australia using financial data. The results in this study indicate it is an effective and competitive alternative to predict business failures in a comprehensible manner. This study also investigates the usefulness of non-financial data derived from auditor's and directors' reports for business failure prediction. The results suggest that the particular non-financial attributes identified are not as effective as the financial attributes in explaining business failures.

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