仿真试验结果表明这种新的模糊支持向量机方法不但有较高的分类准确率，而且对隶属度有很强的预测能力。
Emulational experimental result shows that this new fuzzy support vector machine method not only has higher classified accuracy, but also has stronger test capability for the membership degree.
论文研究模糊支持向量分类机在冠心病诊断中的应用。
In this paper, we have studied on applying fuzzy support vector classification to coronary heart diagnose.
应用模糊理论的方法对支持向量机分类及最优分类面进行了解释，对可疑分类区列出了模糊隶属度的表达式。
A method based on fuzzy theory is applied to explain the classification of SVM and its optimal hyperplane. An expression of fuzzy membership on doubtful classification area is listed.
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