Density weighted support vector data description

作者：

Highlights：

• We present density weighted support vector data description (DW-SVDD).

• DW-SVDD improves classification accuracy by introducing density weight into the SVDD.

• Density weight is relative density of each data points using the k-nearest neighbor (k-NN) approach.

• DW-SVDD prioritizes data points in high-density regions by applying density weight into the search of description of SVDD.

• Experimental results demonstrated that the DW-SVDD improved the classification accuracy.

摘要

•We present density weighted support vector data description (DW-SVDD).•DW-SVDD improves classification accuracy by introducing density weight into the SVDD.•Density weight is relative density of each data points using the k-nearest neighbor (k-NN) approach.•DW-SVDD prioritizes data points in high-density regions by applying density weight into the search of description of SVDD.•Experimental results demonstrated that the DW-SVDD improved the classification accuracy.

论文关键词：One-class classification (OCC),Support vector data description (SVDD),Density weighted SVDD (DW-SVDD),k-Nearest neighbor approach

论文评审过程：Available online 4 December 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.11.025