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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
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