作者: Shifei Ding , Zhibin Zhu , Xiekai Zhang
DOI: 10.1007/S00521-015-2113-7
关键词:
摘要: Support vector machine (SVM) is a machine learning method based on statistical learning theory. It has a lot of advantages, such as solid theoretical foundation, global optimization, the sparsity of the solution, nonlinear and generalization. The standard form of SVM only applies to supervised learning. Large amount of data generated in real life is unlabeled, and the standard form of SVM cannot make good use of these data to improve its learning ability. However, semi-supervised support vector machine (S3VM) is a good solution to this …