The fuzzy membership of each sample is defined by affinity among samples, and by the training determine a threshold, noises and outliers are removed, which influence optimal separating hyperplane.
应用基于样本之间的紧密度确定每个样本的模糊隶属度，通过训练确定阀值，去除影响得到最优分类超平面的噪声和野点。
The fuzzy membership of each sample is defined by affinity among samples, and by the training determine a threshold, noises and outliers are removed, which influence optimal separating hyperplane.
应用基于样本之间的紧密度确定每个样本的模糊隶属度，通过训练确定阀值，去除影响得到最优分类超平面的噪声和野点。
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