Abstract
At present, classification method based on support vector machine can not be used as a decision-making technique yet, but an auxiliary tool for decision-making in practice because the forecasting correct rate of which is difficult to reach as high as one hundred percent. At the same time, SVM method is very sensitive to noise and outlier points. In order to overcome the disadvantages above, a fuzzy support vector machine method for decision-making is presented. By giving different fuzzy factor to different classification samples in SVM, the decision-making hyperplane of each class samples can be obtained, on which the decision can be made in practical system of decision. The simulation demonstrates the effectiveness of this approach.
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