Predicting Corporate Financial Distress Based on Fuzzy Support Vector Machine

In this paper, the fuzzy support vector machine (FSVM) was used to predict the corporate financial distress. First of all, a proper membership model was also proposed to fuzzy all the training data of positive/negative class. Secondly, the outliers were detected by the proposed outlier detection method (ODM). The ODM was a hybrid method based on the fuzzy c-means (FCM) algorithm cascaded with an unsupervised neural network, called self-organizing map (SOM). Finally, FSVM was applied to demonstration research of corporate financial distress prediction, and experimental results indicated that the proposed FSVM actually reduced the effect of outliers and yield higher classification rate than SVM did.