说明：  半监督支持向量机通常直接估算标签未标记实例的分配。 这个即使有最新进展，效率通常也很低在（受监督的）有效培训中支持向量机 在本文中，我们展示了了解以下类别标签的方法未标记的数据与在所有已知标签上受监督的未标记的数据。
(Semi-Supervised Support Vector Machines typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances in the efficient training of the (supervised) Support Vector Machines. In this paper, we show that Support Vector Machines, with knowledge of the means of the class labels of the unlabeled data, is closely related to the supervised Support Vector Machines with known labels on all the unlabeled data.)