A weighted one-class support vector machine

作者：Zhu, Fa^*; Yang, Jian; Gao, Cong; Xu, Sheng; Ye, Ning; Yin, Tongming

来源：Neurocomputing, 2016, 189: 1-10.

DOI：10.1016/j.neucom.2015.10.097

• Weighted one-class support vector machine
• One-class classification
• Neighbors' distribution knowledge
• Instance weights

The standard one-class support vector machine (OC-SVM) is sensitive to noises, since every instance is equally treated. To address this problem, the weighted one-class support vector machine (WOC-SVM) was presented. WOC-SVM weakens the impact of noises by assigning lower weights. In this paper, a novel instance-weighted strategy is proposed for WOC-SVM. The weight is only relevant to the neighbors' distribution knowledge, which is only decided by k-nearest neighbors. The closer to the boundary of the data distribution the instance is, the lower the corresponding weight is. The experimental results demonstrate that WOC-SVM outperforms the standard OC-SVM when using the proposed instance weighted strategy. The proposed instance-weighted method performs better than previous ones.

• 出版日期2016-5-12
• 单位南京林业大学; 南京理工大学