Research on medical diagnostic decision-making based on attribute reduction and support vector machines

The method of attribute reduction is applied to medical diagnostic decision by combining basic theory of support vector machines for nonlinear classification. Decision-making performance of the proposed method is compared with that of the conventional methods. The results indicate our method can decrease the computation complexity and memory requirement a lot, particularly for the large and high dimension data set. Furthermore, the decision-making power remains still good.