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Estimation of the Efficiency of Knowledge Acquisition Techniques Using Clustering

By Pēteris Grabusts and Inese Poļaka

Abstract

Prediction of corporate bankruptcy is a study topic of great interest. There is no general method which would allow one to forecast unfavourable consequence with a high confidence degree. This paper focuses on the analysis of the approaches that can be used to perform an early bankruptcy risk prediction - in previous research multivariate discriminant analysis (MDA), neural network based approach, early potential function method have been used. Lately, time series clustering approach has become popular and its feasibility for bankruptcy data analysis is being investigated. Experiments are performed that validate the use of such methods in the given class of tasks

Topics: bankruptcy, financial ratio, MDA, neural networks, time series, clustering
Publisher: IPME RAS
OAI identifier: oai:ortus.rtu.lv:10344
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